text:
A process control system which includes at least one manipulated variable and at least one controlled variable, provides a method for robust control of a process. Predetermined constraints of the manipulated variables and the controlled variables, and the present values of the manipulated variables are obtained. New values are calculated for the controlled variables for a predetermined number of points in the future, such that the values of the controlled variables are within the predetermined range thereby obtaining an optimal robustness of the resultant controller. The manipulated variables are also calculated to be within predetermined constraints, and the controlled variables to fall within a predetermined range when controllable. From a plurality of solutions, a most robust solution is selected. Then the manipulated variables are adjusted to cause the process control system to drive the values of the controlled variables to the calculated values.
1. In a process control system having a controller for providing robust control to a process, the process further having at least one manipulated variable and at least one process variable, a method for providing the robust control of a process, comprising the steps of:
a) initializing the controller to have predetermined constraints of the manipulated variables and the process variables;
b) obtaining present values of the manipulated variables and the process variables said process variables corresponding to measurement parameters of the process;
c) calculating new values of the process variables for a predetermined number of points in the future in order to have the values of the process variables within the predetermined range to obtain an optimal robustness of the resultant controller, the manipulated variables being within predetermined constraints, and the process variables falling within a predetermined range when controller; otherwise, keeping process variable constraint violations to a minimum;
d) from a plurality of solutions, selecting a most robust solution; and
e) controlling the process in accordance with the most robust solution.
2. In a process control system, a method for providing robust control of a process according to claim 1, wherein the step of controlling comprises the steps of:
a) outputting the manipulated variables of the most robust solution of step (d) of claim 1 to the process; and
b) adjusting the process in response to the manipulated variables to cause the process control system to drive the values of the process variables to the calculated values of step (d) of claim 1, thereby providing the control of the process.
3. In a process control system, a method for providing robust control of a process according to claim 2, wherein the step of selecting comprises the step of:
a) determining a set of controlled variables which correspond to minimum controller magnitude.
The present invention relates to control systems, and more particularly, to a method of robust multivariable predictive control (RMPC) techniques utilizing range controls.
In present day process control systems, many techniques are presently in use which utilize model predictive control techniques which control process variables to predetermined setpoints. Oftentimes the setpoints are a best estimate by the system operator of the value of the setpoint or set points. When a process is being controlled to a setpoint, the controller may not be able to achieve the best control performances, especially under process/model mismatch.
In order to enhance the controller performance, there is a need to provide a method for controlling a process which controls the process variables (i.e., controlled variables) by commanding each manipulated variable associated with the controller of the process control system to a corresponding range, i.e., each control specification having an upper bound and a lower bound, The result is that the Frobenius norm of the controller is minimized and thus the process is controlled within the desired tolerance of the product specification, the impact to the system is reduced, and results in a more robust controller.
Therefore, there is provided by the present invention, a controller which controls each controlled variable of a process to be within a corresponding predetermined range. A process control system includes at least one manipulated variable and at least one controlled variable. A method which provides robust control of a process, comprises the steps of initializing the robust control to have predetermined constraints of the manipulated variables and the controlled variables. The present values of the manipulated variables and the controlled variables are then obtained. New values are calculated for the controlled variables for a predetermined number of points in the future, such that the values of the controlled variables are within the predetermined range thereby obtaining an optimal robustness of the resultant controller. The manipulated variables are also calculated to be within predetermined constraints, and the controlled variables to fall within a predetermined range when controllable; otherwise, to keep the controlled variable constraint violations to a minimum. From a plurality of solutions, a most robust solution is selected. Then the manipulated variables are adjusted to cause the process control system to drive the values of the controlled variables to the calculated values.
Accordingly, it is an object of the present invention to provide a more robust controller for a process control system.
It is another object of the present invention to provide a more robust multivariable predictive controller.
It is still another object of the present invention to provide a more robust multivariable predictive controller wherein each controlled variable of the process is controlled to be within a range having an upper bound and a lower bound.
These and other objects of the present invention will become more apparent when taken in conjunction with the following description and attached drawings, wherein like characters indicate like parts, and which drawings form a part of the present application.
FIG. 1 shows a functional block diagram of a process control system in which the present invention may be utilized;
FIG. 2 shows the system of FIG. 1 which effectively includes three sub-controllers; and
FIG. 3 shows a timing diagram of an application of the range control formulation of the present invention.
Referring to FIG. 1, there is shown a functional block diagram of a process control system in which the present invention may be utilized. A controller 10 has multiple outputs, which are coupled as input variables u to a process 20. The process 20 can include, for example, a plurality of elements which can be controlled such as valves, heaters, . . . Process variables y of process 20 include temperature, pressure, level, flow, . . . which govern product quality. The input variables (or manipulated variables) u, are defined as: ##EQU1## and the output variables (or controlled variables) cv, are defined as: ##EQU2## Thus, the process 20 is a dynamic process P(s) having m manipulated variables and n controlled variables. The controlled variables (cv) include n1 regulated cv, n2 restrained cv, and n3 optimized cv. Generally,
In the present invention, the control specification, r, (this is referred to as setpoint in previous systems) is defined as follows: ##EQU3##
For the regulated cv, the lower bound is equal to the upper bound, r1 =r1. For the restrained cv, the upper bound is greater than the lower bound, r1, >r1, or there is either a lower bound only or there is an upper bound only. Finally, for the optimized cv, there is no bound at all.
Referring to FIG. 2, there is shown the system of FIG. 1, which effectively includes three sub-controllers 11, 12, 13 to handle the three cases identified above. The range control function of controller 10 is formulated to handle the three cases identified above in accordance with: ##EQU4## Subject to: MV≦x≦MV, and
where, W is a user weighing matrix;
A is a matrix (aij coefficients) that relates the process dynamics of an output to an input; y is range variables (extension of setpoint); and x is the manipulated variable u or Δu (i.e, Δu=uCURRENT -uLAST), depending on application. PV and PV (process variable) is the range it is desired to have the process operate, and MV and MV is the range physical limits it is desired to have the process operate.
The controller has to find not only a best solution x, the movements of the manipulated variables u, but also must find an optimal point at which the process should be operating within the range, i.e., within the high-low-bound.
The solution to the formulation of the controller can result in one of three cases.
Case 1--there is a unique solution (of x*, y*) and Ax*≠y*;
Case 2--there is an infinite number of solutions (x*, y*) and Ax*=y*; and
Case 3--there is an infinite number of solutions (x*, y*) and Ax*≠y*.
Most of the solutions fall within Case 2 or Case 3. Case 1 indicates the process is not controllable.
For Case 2 and Case 3, it is desirable to find the most robust solution, i.e., find the solution which gives the smallest risk under model/process mismatch, which generally is the smallest move. Thus, for Case 2 and 3, it is desired to minimize the upper bound of the maximum singular value of the controller, ##EQU5## such that x*=Q�(predicted error) where Q is the controller matrix, qij are the elements of the controller matrix Q, i.e., minimize the norm of the controller. Norm is the measure of the magnitude of the controller, i.e., an extension of the controller gain. In multivariable cases, the concept of gain is lost. Mathematically the gain is described by the "maximum singular value" or its upper bound, i.e., a Frobenius norm. Thus, the solution which corresponds to the smallest magnitude of the controller is found. This results in a greatly enhanced robustness of the controller.
As a result of the added complexity but increased advantages, computational load on the controller 10 is increased. In order to achieve added robustness and to handle PV constraints, the controller needs to compute where the manipulated variables should be and also where the controlled variables (cv) should be. The controller 10 solves a "staged" non-linear programming problem. First, the range control formulation is solved, and second (for a Case 2 or Case 3 solution) solve to minimize the magnitude of the controller. The programming can be converted into a "staged" semi-positive quadratic programming (QP) solution, well known to those skilled in the art.
Referring to FIG. 3, there is shown a timing diagram of an application of the range control formulation of the present invention indicating a versatile performance feature. Here the process variable has a range. The process variable has a process variable upper and lower bound PV and PV, respectively, specified by the user. Similarly, as discussed previously, the user specifies the upper and lower bounds for the manipulated variables (MV)(not shown). The current time is shown as t=0 and for each PV, in this example, there are five (5) PV values predicted ahead. If there are 20 PVs, then 100 PV values are to be entered, No. 1 thru 5 PV value pairs for the first PV, No. 6 thru 10 PV value pairs for the second PV, . . . and finally No. 96 thru 100 PV value pairs for the twentieth PV. Thus, PV1, and PV1, PV2 and PV2, PV3 and PV3, PV4 and PV4, and PV5 and PV5 values are entered by the user in this example. Here, in order to achieve robustness, the MV values are assumed to hold unchanged. The solutions of the range control formulation are y*1, y*2, y*3, and y*4, y*5. Each of the solutions y* are within the PV bounds specified. By specifying a "funnel" (the specification of the PV high and low boundary), then a number of solutions are obtained because the trajectory can be anywhere within the funnel, and the one solution which corresponds to the least magnitude of the controller is determined.
Thus, the Range Control formulation handles all controlled variable constraints dynamically, even if the number of constrained controlled variables is greater than the number of manipulated variables, and exhibits greater control robustness.
Attached hereto as appendix I, is a paper entitled "Range Concept and Range Control Formulation", pages 1 through 19, which includes the detailed mathematics to support the detailed description section of the specification.
While there has been shown what is considered the preferred embodiment of the present invention, it will be manifest that many changes and modifications can be made therein without departing from the essential spirit and scope of the invention. It is intended, therefore, in the annexed claims to cover all such changes and modifications which fall within the true scope of the invention.
For most MIMO control applications, there are often more PVs of control interest than MVs available to manipulate. Fortunately, most PVs of control interest are the PVs to be controlled within two distinct high and low constraints (or bounds). Those PVs are referred to as restrained PVs. There are usually no control performance required as long as the restrained PVs are within there bounds. For this reason, the restrained PVs can and should be treated differently form the traditional CVs (Controlled Variable) in order to gain additional control robustness that is often more desired than holding (in prediction) a selected number of restrained PVs straight lines within their physical constraints. Since the acronym "CV" (Controlled Variable) has been associated with a vague concept that we will further subdivide, it seems to be a good idea to extend the definition of CV and define two new subcategories under Controlled Variables.
______________________________________Definition Meaning______________________________________Controlled Variable PVs of control interestRegulated Restrained Regulated: PVs to be controlled at setpoints Restrained: PVs to be controlled within bounds______________________________________
Note that under this extended definition, the meaning of Controlled Variables is no long limited to the PVs to be controlled at their (internal or external) setpoints as implied or defined in many MIMO controller packages. Note also that one can further define subcategories in parallel to Regulated PVs and Restrained PVs, or as subcategories of either Regulated PVs or Restrained PVs.
It is noteworthy that, in this extended definition of the CV, the Regulated PV is just a special case of the Restrained PV, where the high and low bounds happen to equal to each other and become an equivalent setpoint. This yields a mathematically convenient range control formulation. In other words, the range control algorithm is formulated on the concept of range-the high/low bounds. The regulation at setpoint is treated as a special case, therefore the tasks of regulation and constraint handling are mathematically unified.
In general, the process model is a non-square system. Suppose the process is m-input-n-output system, or nxm system. And the vast majority of the process control task can be represented as follows,
n1 outputs of the system are desired to be regulated (or controlled at setpoint), n2 outputs are desired to be controlled within their high-low bounds (some of those bounds can be infinite). Within the second category, n3 of n2 outputs are to be optimized (either minimized or maximized) with or without bounds.
Suppose the model can be described by finite step responses of multiple inputs, we can always represent the changes of multiple outputs in the following form,
Δpv=A Δmv
where A is N�M matrix. N=n*(prediction points); M=m*(mv blocking points).
Furthermore, we would like to find most control-robust moves to achieve regulations on the n1 regulated process variables, maintain the n2 restrained process variables within their bounds respectively and, if possible, move the n3 optimized process variables to an optimum.
The controller to achieve the above tasks can be described referring to FIG. 2.
Where "robust regulatory controller," "robust restrained controller" and "dynamic optimizer" represent three different sub-controllers. Each sub-controller is discussed as follows,
First, the on-line portion of robust regulatory controller and robust restrained controller can be formulated in following generic form,
For all vector Δmv RM and a dynamic system matrix A RN�M, the corresponding change in outputs, A�Δmv, forms the range space of A. When Δmv is constrained in a box Bmv (called my-box), i.e., x1i ≦Δmvi ≦xui, for i=1 . . . M, A�Δmv forms a convex region RA in space RN.
At any particular time interval in control, the predicted output changes, Δpv RN, are, if possible, desired to be restrained in a predefined box Bpv (called pv-box), y1j ≦Δpvj ≦yuj, j=1 . . . N For those regulated process variables, y1j =yuj, and for others, -∞≦y1j ≦yui ≦∞.
Geographically, the control task is to find, if Bpv ∩RA={0}, the shortest distance (usually weighted) between two regions Bpv and RA, or, if Bpv ∩RA≠{0}, the most control-robust moves (for instance, ∥Δmv∥2 -minimized solution) so that A�Δmvsolution Bpv.
Let x denote Δmv and y denote Δpv
Mathematically, the controller is formulated as ##EQU6## subject to x1i ≦xi ≦xui, i-1 . . . M
Where aj is the j-th row of A and Φ is define as φ(z, 1, u)= ##EQU7## and wj >0 is a positive weight for j-th PV violation.
If multiple solutions exist, find the one that obtains the most robustness. For the sake of readability, the ∥x∥2 -minimized solution is used here. ∥Q|fro- minimized solution is discussed in next section, where Q is the MIMO controller.
This mathematical representation of range control formulation presents a number of advantages:
(a) It does not specify "at will" where within their bounds all the process variables should be at, except those regulated process variables. Instead, it lets the controller to figure out where the best place they should be at in order to gain control robustness or minimize the ∥Q|fro.
(b) It allows the control designer to specify a pair of tighter high/low bounds for a regulated process variable at the end of the prediction horizon, and to specify a pair of looser high/low bounds for the same regulated process variable at the beginning and in the middle of the prediction horizon.
The computer realization of the controller formulation (3.3.1) can be devised by the following two steps corresponding to the first two sub-controllers, robust restrained controller and robust regulatory controller in the FIG. 3.1.
1) The task of the restrained controller is to test if Bpv ∩RA={0} and yield solution accordingly. The following Quadratic Programming (QP) problem is solved to find MV moves to minimize predicted PV violations. ##EQU8## subject to x1i ≦xi ≦xui, i=1 . . . M; and
y1u ≦yj ≦yuj, j=1 . . . N.
Where W=Diagonal([w1 . . . wN ]) is the diagonal weighting matrix. Denote the solution to (3.3.2) as (x*, y*), and define D*=Ax*-y*. If D*≠0, then Bpv ∩RA={0}. And multiple solutions could still exist. Then, ##EQU9## subject to x1i ≦xi ≦xui, i=1 . . . N
Ax-y=D* (D* is the optimal violations); and
y1j ≦yj ≦yuj, j=1 . . . M.
Then x3.3 * to (3.3.3) is the controller MV moves for that time interval. Note that only when Bpv and RA have parallel and kissing boundaries should solution to (3.3.3) differ from that to (3.3.2).
2) When D*=0, meaning Bpv ∩RA≠{0}, and multiple solutions to (3.3.2) exist. The robust 2-norm-minimized solution can be found. (For ∥Q∥fro minimized solution, see next subsection.) Its task is defined as follows, ##EQU10## subject to x1i ≦xi ≦xui, i=1 . . . M, and
y1j ≦aj x≦yuj, j=1 . . . N.
One of the most important advantages of the range control algorithm is that the resultant controller tries to control as many CVs as possible. The control performance on restrained PVs are essentially same as that of the regulated PVs. The user does not have to specify explicit CVs and implicit CVs (or recoupled CVs and undecoupled CVs).
Another obvious advantage is gaining additional robustness without any model uncertainty descriptions. The gain of robustness is based on the fact that there are often infinite number of solutions to the range control problem (3.3.2).
It is noteworthy that range control algorithm does not differentiate the regulatory controller from restrained controller. However, the off-line rain-max algorithm does treat the two controllers differently when robust stability and robust control performance are considered. The fundamental difference lies in the fact that the regulatory controller alone is a linear controller after all, but the restrained controller is not. Therefore the combination of the two are not linear, since the restrained controller interact with the regulatory controller.
Given a limited computing resource, the main numerical difficulties for range control algorithm are as follows,
1) The size of the original formulation (3.3.2) is much bigger than conventional control formulations. The range control formulation is in the space of R.sup.(N+M), while conventional control is in the space of RM. Notice that N usually ≧M and that CPU time required for QP problem is usually proportional to (size)2 ˜(size)3.
2) The additional control robustness comes from finding the best solution when there are multiple (usually infinite) solutions. It adds additional complexity to the numerical solution technique.
3) The resultant controller becomes nonlinear, at least piece-wise linear. It adds significant difficult to off-line robust control design.
On the other hand, this range control formulation possesses some mathematically-convenient features that conventional control formulations may not have. Those features are as follows,
1) The constraints in formulation (3.3.2) are all simple bounds. There are many useful numerical treatments can be employed to simplify the numerical procedures.
2) Many terms in formulation (3.3.2) may vanish at the solution. Thus not all the terms need to join the iterations.
3) The most control robust solution will be found under the condition of multiple solution. This helps significant to reduce the sensitivity of blocking to the final control solution. Also, there is little need for specifying initial part of the internal trajectory.
Norms and scaling almost always work together. Without proper scaling, norms could be misleading; without a proper norm definition, a control formulation can hardly yield the robustness to counteract all possible uncertainties.
For any MIMO controller, it can be expressed in a matrix form as follows,
ΔMV=Q Δe
Where ΔMV is the predicted MV moves and Δe is an error term.
For the range control algorithm, the error calculation is slightly different. The final goal is to find a robust MV move that satisfy the following,
Thus, the change in error Δe should be calculated as follows (see Theorem 1 for more rigorous expression), ##EQU11## where ΔYBi and ΔYBi are i-th high and low PV a-bounds respectively, and yi is the predicted i-th PV (in H matrix arrangement).
There are three norms involved in RMPC controller as follows,
1. Maximum singular value of the RMPC controller
2. Frobenius norm of the RMPC controller
3. 2-norm of control moves by RMPC controller
The first two are matrix norms and the third is a vector norm. They are closely related. However their relationships are not always straightforward. (Golub and Van Loan)
Minimizing the controller's maximum singular value (the controller norm) is the final goal. But this task is too difficult to tackle at every execution time on-line. Frobenius norm is a good, close upper bound of the maximum singular value when properly scales. And, minimizing Frobenius norm of the RMPC controller is much less expensive CPU time-wise.
The unweighted robust control solution will yield a default control performances on each CV (including Reg and Res PVs). It is often desired, from the user's stand point view, to minimize the maximum singular value of a weighted RMPC controller. The weights allow the user to specify mainly two things: 1) the relative control performance on each PV of control interest; and 2) to use which MVs more to control which CV.
A weighted Frobenius norm of the RMPC controller is then the upper bound of the weighted maximum singular value. When such a solution exist (the closed-loop system has no sustained constraint violations), it can be expressed as follows,
Let Q=[qij ]M�N, and wij ≧0 ##EQU12## subject to ΔYB≦H Q Δe≦ΔYB where Δe can be expressed as follows, ##EQU13##
Denote H- as the collection of the rows in H that are binding at the solution to (3.4.1). Denote Q- as the collection of the corresponding binding columns in Q. Note that the rest of columns in Q are all zeros. Then, (3.4.1) can be rewritten equivalently as follows,
Let Q=[qij ]M�N, and wij ≧0 ##EQU14## subject to H- Q- =I (an identity matrix)
Theorem 1:
If the weights are all equal, wij =w, ij, then (3.4.1) is to minimize the Frobenius norm of matrix Q or (3.4.2) is to minimize the Frobenius norm of matrix Q- ; and the solution
1) is equivalent to minimizing the 2-norm of the MV moves, ∥ΔMV∥2.
2) can be expressed as follows
where H- is collection of the rows of H that are binding at the solution to (3.4.1).
Q can be constructed from Q- by adding zero-columns to the corresponding positions where H has non-binding rows.
Denote Q- =[q1,q2 . . . qp ]rxp =[qij ], (r=M>p) the (3.4.2) can be rewritten as, ##EQU15## subject to H- Q- =H, [q1,q2 . . . qp ]=[e1,e2 . . . ep ]=I pxp.
Notice that the constraints are separable in terms of qj that is squared and summarized in the objective function, thus the original minimization problem is equivalent to the following p sub-problems: ##EQU16## where ej =[0 . . . 0 1 0 . . . 0]T is an r�1 unit vector.
For each sub-problem, say, j=k, the solution to (3.4.3) is as follows, (Golub & Van Loan, 1985) ##EQU17## here ui, vi and σi are from the singular value decomposition of H- as follows,
where U=[u1, u2 . . . ur ], V=[v1, v2 . . . vp ] and Σ=[diag(σ1, σ2 . . . σp), 0].
Note that H- can also be reconstructed as (3.4.5): ##EQU18## where Up, Vp and Σp are partitions of U, V and Σ, Up =[u1, u2 . . . up ], Vp =[v1, v2 . . . vp ] and Σp =diag(σ1, σ2, . . . σp).
Furthermore, qk in (3.4.4) can be rewritten as follows, ##EQU19## and the optimal solution Q- can be constructed as follows, ##EQU20##
Note that H- T [H- H- T ]-1 Δe- is also the solution to minimizing ∥ΔMV∥2 subject to the same set of constraints as follows ##EQU21## subject to H- ΔMV=Δe-
Thus, solution to (3.4.7) is the same of that to (3.4.1).
When weights in (3.4.1) are not equal, the vector 2-norm of control moves and Frobenius norm of the controller are related, but in a much less obvious fashion.
The purpose of scaling is twofold. 1) improve numerical "behavior" of the working system; 2) make the norms more meaningful. Both tasks can be achieved by decreasing or even minimizing the condition number of working matrix with scaling. In a very general form, scaling can be performed by ##EQU22## where H is the original model matrix, Hs is the scaled working model. Dr is a left transformation matrix, and Dc is a fight transformation matrix. One drawback with this approach is the lack of efficient algorithms to compute (3.4.*1), since the condition number is a very complex function of Dr and Dc.
One efficient algorithm was found when Dr and Dc are reduced to be diagonal matrix, Dr for row scaling and Dc for column scaling. Note that the condition number of Hs is still a very complex function of Dr and Dc.
Note that Dr and Dc can be a good sized vectors. It is almost infeasible CPU time-wise to search in [Dr, Dc ] space since condition number is a fairly expensive function to be computed in the gradient and Hessian matrix. A special optimization algorithm is formulated for (3.4.*1). Its search steps are based upon the following algorithm to improve convergence dramatically. At k-th iteration, ##EQU23## where hri and hcj are i-th row vector and j-th column vector of H respectively. The iteration stops when cond(H) can not be improved. In about 50 test cases with different matrix size, it take 2-5 steps to reach an optimum. The longest is 12 steps with tolerance is set to be 1E-4.
Compare this approach with the ones recommended or used in LINPACK, this new approach gives better scaling or small cond(Hs). The speed is comparable to the LINPACK's simple non-optimal scaling, and dramatically faster than LINPACK recommended optimal scaling.
The following is an real-life example, H is the FCCU Cat-Cracker gain matrix
______________________________________H = -0.0230 -0.0250 0.0560 0.1900 -0.0175 0.1900 -0.0100 -0.0600 0.2750 2.3500 1.0000 1.2900 0 0 0 2.0400 -0.0050 -0.0200 0.0080 0.0106 0.2000 3.1500 -0.0100 -0.0120 0.1450 12.8000 -12.1600 -7.6700 0.3690 29.2500 -16.8400 -13.2900 0.1580 -2.4500 7.4800 5.8900Hs = 1.2838 -0.1418 0.6066 1.3978 -1.2482 1.3773 -0.1384 -0.5640 1.2178 1.0577 0.8594 0.7530 0 0 0 2.0563 -1.6765 -0.6816 0.5205 0.4684 1.0298 1.6485 -0.0100 -0.0081 0.1033 0.9269 -1.6813 -0.7203 0.1569 1.2641 -1.3896 -0.7448 0.1960 -0.3089 1.8010 0.9632Dc = 0.3015 0.0306 0.0585 0.0397Dr = 185.13 236.57 14.688 25.367 1112.1 17.079 2.3632 1.4104 4.1152cond(H) = 206.18cond(Hs) = 2.3634______________________________________
Notice that the elements in the scaled Hs is much more evenly distributed, meaning all elements get closer to unity. And the condition number of Hs is much smaller than that of H.
It is also noticed that scaling on the full dynamic matrix does not provide much additional advantages over scaling on just the gain matrix and then scale the dynamic elements the same way as their gain element. The primary reason is that gain is part of dynamics and each SISO portion is always somewhat parallel. For RMPC, is seems to be a good idea to obtain the scaling just based on gain matrix, then apply the scaling to all dynamic element. The optimal scaling will be done off-line. On-line it will "merge" with the user weights (scaling) and apply to the H matrix.
RMPC user may wish to use some MVs relatively more than the others, or to have relatively less constraint violations of some PVs than that of others. It is necessary to provide a user weighting on top of the optimal internal scaling. The user MV weighting can be directly applied (multiplied) to Dc. However the user PV violation weighting should ideally be applied (multiplied) to Dr only when there is sustained violation.
A note: User PV weighting can be interpreted as relative control performance weighting as well, since PV weighting are always effective on regulated CVs and PV weighting on restrained CV are effective when PV constraints are violated.
It is desired to give the user some indication what the RMPC controller is doing at any time. An easy indication is to display the status of the controller. The status used in DPC seems to be well accepted by the operators and plant engineers. They are as follows,
______________________________________Status Full Name Meaning______________________________________OFF control is not Only data acquisition is on. onINIT INITializing Initialize RMPC downstream controllers.REG REGulating No active restrained PV constraints.OPT OPTimizing All PVs are within HI/LO bounds.CNS CoNStraint At least one restrained PV is constrained. handlingCCF Constraint Handling constraint conflicts. ConFlictingCMV Constrained MV constraints are excessively stringent. MV______________________________________
The following are detailed description of the RMPC Controller statuses
1. OFF status indicates that the RMPC Controller is not on-line, but the data acquisition part of the RMPC Controller is still running and displaying the current PV and MV values.
2. INIT status indicates that the RMPC Controller has just turned from the mode OFF to ON. The RMPC Controller initializes itself and establishes the connections with the downstream controllers. Normally, the RMPC Controller should show the INIT status for only one execution interval. Exceptions can arise when the downstream controllers are not ready at the end of that execution interval. The RMPC Controller waits and remains in the INIT status for a predetermined number of execration intervals.
3. REG indicates that the RMPC Controller is controlling the regulatory PVs to their setpoints. The Regulatory Controller functions as long as the RMPC Controller is set ON. The REG status is always active but only displays when the following two conditions are both satisfied:
None of the restrained or optimized PVs have any active constraints
Optimizer move size is set to zero, or at least one of the regulatory PVs is outside its regulatory band region.
When both conditions are met, the REG status displays.
If one of the regulatory PVs is outside its regulatory band region, the Regulatory Controller takes precedence and the Dynamic Optimizer is set in a waiting mode. This may not seem meaningful when the RMPC Controller is running on the perfect model process in simulations. However, when there is model-process mismatch, the RMPC Dynamic Optimizer is prevented from pushing the process too aggressively. This safeguards the optimizer move-size, and reduces the retuning effort when model-process mismatch becomes significant.
The OFT, CNS, CCF and CMV statuses are mutually exclusive; that is, only one of them can be a valid status at a time. The regulatory control status is implied when the OFT, CNS, CCF and CMV statuses display. Therefore, when the REG status displays, it also indicates that none of the OFT, CNS, CCF and CMV statuses are active.
4. OPT status indicates that the RMPC Controller is optimizing the process operation according to the economical objective (see Equation (3). This status will be displayed only when:
None of the Restrained or Optimized PVs have an active constraint.
Optimizer move size is set to a positive value.
None of the regulated PVs are outside their regulated band regions. Regulatory control is implied.
5. CNS status indicates that the RMPC Controller is handling the predicted or actual constraint violations of the restrained and optimized PVs. It serves as an early warning when the violations are predicted. Internally, the RMPC Restrained Controller is activated and the Dynamic Optimizer is set in a waiting mode. Regulatory control is implied.
6. CCF status indicates a special subset of the CNS status when RMPC detects that at least a pair of the severely conflicting constraints is active and special algorithm is employed to handle that. This status is rare since most of the conflicting constraints can be resolved in the robust fashion within the predicted horizon under the CNS status.
The CCF status usually comes with an abnormal situation: one of the major MVs is lost, for instance, or one PV measurement is exceedingly biased, causing an excessively constrained situation. Internally the Restrained Controller minimizes the weighted violations. CCF is a (somewhat) predicted indication, and it usually comes on for a few execution intervals and goes away. In a noisy environment, it could come and go a few times.
When CCF displays, some engineering assessment is recommended to both identify the cause and to resolve, if necessary. This could be extremely helpful in the commissioning phase of the RMPC project. It is possible to introduce an artificial pair of conflicting constraints by specifying some stringent high or low constraints.
Regulatory control is implied. However, there might be an offset if the CCF status persists.
7. CMV status indicates that them are too many excessively stringent MV constraints for the RMPC Controller to function normally. This status displays when there are fewer unconstrained MVs than the number of regulated PVs.
The CMV status warns that too many downstream controllers have been turned off.
Regulatory control is implied. However, there might be an offset if the CMV status persists.
Patent Citations
Referenced by
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Original Image


text:
Ray Rice and Torrey Smith won NFL awards the night before the Ravens take on the 49ers in Super Bowl XLVII.
Rice's wild catch-and-run that helped the Ravens convert on a fourth-and-29 late in the fourth quarter against the Chargers and was picked as the NFL's top play of the year.
He took a short pass from quarterback Joe Flacco and ran through the San Diego defense to just barely make a first down. Rice started near the right sideline and weaved his way to the other side of the field and kept Baltimore alive. That was the key play in a drive that led to a game-tying field goal.
The Ravens later won it in overtime, a crucial victory this season.
Smith won the league's "Never Say Never" Moment of the Year for his performance in the Week 3 win over New England in Baltimore.
Smith's brother had been killed in a motorcycle accident earlier that weekend and, even though the Ravens gave him permission to sit out the game, the second-year receiver came up big with six catches for 127 yards and two touchdowns. His emotional performance helped the Ravens edge New England, 31-30, in front of a national TV audience.
His effort got picked from five finalists by voters on NFL.com/gmc.
The Ravens now hope to fare just as well in Sunday's game.

subset: commoncrawl


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A man arrested earlier this week on ATM vandalism and assault charges was charged again Thursday when police learned that he was in possession of a stolen vehicle, police said in a news release.
Brandon L. Miller, 26, 415 Cash Hollow Road, was charged with possession of stolen property over $5,000.
Police said when Miller was served with several felony arrest warrants for unrelated charges, Miller was found in possession of a vehicle reported stolen by the Sevier County Sheriff's Department.
Miller remained jailed Friday in the Washington County Detention Center with $10,000 bond in addition to the $72,000 bond he had from previous charges.
Miller already was jailed on charges stemming from a series of events in Elizabethton and Johnson City that included two attempted ATM break-ins and an assault.
The first incident occurred around 3:30 a.m. Tuesday at Carter County Bank's ATM at 1254 Milligan Highway. Miller and Cari Marlene Davis, 22, 136 Brobeck Road, Limestone, were each charged with attempted theft of property over $10,000 and vandalism over $1,000 in that incident.
Miller also was charged with attempting to break into the Citizens Bank ATM at CVS, 4211 N. Roan St., and with assaulting Davis at the the Shell gas station, 2607 S. Roan St., that same morning.


text:
JEEP: 1972 Commando, superb, fully-restored V8 Jeep convertible, in blue. Hyman Ltd, 314-524-6000, MO; complete details at: www.hymanltd.com... More
Kaiser Jeep reintroduced one of its most popular vehicles the Jeepster in 1967 to supplement its very successful production of medium duty military trucks... More
JEEP: 1968 Commando convertible, a gorgeous example, red with black interior and manual transmission. Hyman Ltd, 314-524-6000, MO; details at: www.hymanltd.com... More


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Brent Batten: Georgia Hiller in the middle of a dog fight
Since its creation in 2001, Rover Run at Veterans Community Park has been a hit with dogs and their owners.
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Category: Chicopee RSS
3 women plead innocent to prostitution-related charges following raids on massage parlors in Longmeadow, Hadley
November 05, 2009, 1:59PM
Raids were conducted at salons in Springfield, Hadley, Chicopee, West Springfield, Longmeadow and East Longmeadow. Full story »
Longmeadow massage parlor owner pleads innocent to prostitution-related charge
November 05, 2009, 12:43PM
Xiuli Li, 48, of Springfield was ordered held in lieu of $5,000 cash bail Full story »
Despite historic ballot, Springfield voter turnout lowest among 8 Pioneer Valley cities holding mayoral elections
November 04, 2009, 11:36PM
Chicopee, Holyoke, Westfield and West Springfield had voter turnout of 35% or less. Full story »
Mohegan Sun officals tout potential jobs, other benefits of proposed Palmer casino
November 04, 2009, 11:28PM
Peter J. Schultz, Mohegan Tribal Gaming Authority project coordinator, hosted the 2nd "community conversation" in Chicopee. Full story »
Members of Assumption of Blessed Mary Church in Chicopee appeals closure plans by Roman Catholic Diocese of Springfield
November 04, 2009, 9:00PM
Nine out of 19 churches in Hampden and Hampshire counties identified for closure have filed appeals. Full story »
3 women arrested on prostitution charges as police raid 8 massage parlors in Hampden, Hampshire counties
November 04, 2009, 8:10PM
Six other people were arrested on immigration charges. Full story »
Police raid 2 Hadley massage parlors reportedly associated with others in Chicopee, Springfield
November 04, 2009, 4:05PM
Law enforcement officials also raided the Chinese Massage Therapy parlor at 271 Belmont Ave, Springfield. Full story »
Chicopee Mayor Michael Bissonnette easily wins 3rd term as mayor
November 03, 2009, 8:52PM
The vote was 7,610 for Bissonnette to 3,531 for Shane Brooks. Full story »
Judge says Springfield violated Mass. bidding laws in construction of Thomas J. O'Connor Animal Control Center
November 03, 2009, 6:57PM
The Appeals Court sent the case back to Hampden Superior Court for entry of a new judgment that voids the city's lease. Full story »
Holyoke, Chicopee voters cast ballots
November 03, 2009, 10:47AM
Poll workers say they are pleased with the early turnout. Full story »
Election Day dawns clear and bright for Western Massachusetts
November 03, 2009, 8:46AM
Violent crime was on the minds of a number of Springfield voters as they headed to the polls Tuesday. Full story »
Chicopee voters to decide races for mayor, city council
November 02, 2009, 5:45PM
City Clerk Keith Ratell is predicting a 38 to 40 percent turnout Full story »
Police identify Westfield stabbing victim as Christopher Mattoon of Springfield
November 02, 2009, 12:22PM
Mattoon was treated and released from Baystate Medical Center. Full story »
Springfield firefighter arrested by city police following domestic assault
November 02, 2009, 11:48AM
Juan DeJesus, 39, of 26 Gold St., was charged with assault and battery, police said. Full story »
Mayoral contests highlight elections of 2009 ballot
November 02, 2009, 10:07AM
Read our round-up of the local races before you head to the polls tomorrow. Full story »


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Monthly Archives: August 2006
Beyond the Cliff
Along the far side of the Golden Gate Bridge, in Marin Headlands, past the initial fortifications, you can follow a trail down to Kirby Cove. A little way down this trail is a side path that takes you to some World War II vintage fortifications. Unlike the vista points above, there are no fences here to stop one from scrambling down the cliffs. So you can make your way down a ways, for this direct view of the Golden Gate Bridge rises from the cliffs (double-processed from the RAW for the darker cliffs and the lighter bridge against the sky).
Click here for an image from above of the Golden Gate Bridge at dusk, one after dark, and looking out the Golden Gate from above Kirby cove by moon-and-star light.
Origins of Life
Close up, these water drops on a web look like amoebas or some other primitive creatures to me. But in this photo, the water is evaporating, and you can pierce the veil to see the web:
View this photograph larger.
By the way, "piercing the veil" is a legal expression describing what you have to do to get at the human malefactors who may hide behind a corporate facade. It's fun to use a legal trope to decribe water drops in my garden!
A Pixel Is a Pixel
I post-processed this photograph of the Golden Gate Bridge by early moonlight from Fort Mason by sandwiching four different conversions from the RAW negative using Photoshop layer masks and the Paintbrush tool.
Recently, Reuters photographer Adnan Hajj was in the news when he was fired for manipulating a photo of Beirut being bombed by an Israeli air raid. Based on the photos published in the New York Times story, Hajj used a clone tool to crudely amplify the plumes of smoke coming from downtown Beirut. It's not clear whether the purpose of the digital manipulation was politically based, or rather (more likely) to make the manipulated photograph more salable.
These two photographs (mine and Hajj's picture of Beirut burning) are very different in content and purpose. Why do I bring the digital manipulation of these two wildly divergent photographs up in the same story?
Because all digital photographs are manipulated, either by software or the software's operator. A pixel is a pixel. The processor in a digital camera manipulates the photo when it captures and saves a RAW image, and manipulates it more if it converts it to the JPEG format. And a photographer with the time, effort, and skills can "paint" a photograph pixel by pixel. Or use higher-level tools to paints pixels with greater efficiency and subtlety. As I did in my photo of the Golden Gate Bridge and Adnan Hajj did in his photo of the war in the Middle East.
So all digital photos are manipulated. What are the morals of this sea change for photographers, photo editors, and those who simply look at photos?
For photographers, just because you can manipulate an image doesn't mean that you should do so. There's a different duty of care and responsibility on a news photographer like Adnan Hajj, whose goal is to is to accurately portray current events, than there is on me since my goal is to produce aesthetically pleasing images. At the very least a photographer should be prepared to state whether an image has been manipulated in post-processing. Furthermore, if an image is represented as an accurate portrayal, then any manipulation should be "honest."
I am prepared to state right now that every single photograph of mine has been manipulated. Can we all say together that digital captures straight from the camera don't look terribly good? Unmanipulated digital photographs miss nine tenths of the potentiallity of this exciting new medium, which combines photography with digital manipulation.
Of course, if you grant that some post-processing manipulation is required for all photographs, honesty in this manipulation is a very subjective matter. This puts photo editors in a very tough position. In the New York Times article about the Adnan Hajj affair, Jonathan Klein, the chief executive at Getty Images, the world's most important stock photo agency, is quoted as saying that the only way to avoid problems like the Hajj manipulated photos is to "employ people of integrity" and if there are abuses "not only take action, but take visible action."
Making an example of digital malefactors is shutting the barn door after the equine creatures, digital or otherwise, have escaped. It won't really stop the problem. In the case of the Adnan Hajj photos, the manipulation is pretty obvious at sight to anyone who is familiar with way cloning works. So photo editors need to be better educated about how software like Photoshop works, and how to spot manifestation of manipulation.
It sounds like one of the reasons that the Adnan Hajj photos got published was that the process was rushed. Slowing down and really looking is a partial solution to this issue. More important, organizations that are vouching for the verasimiltude to life of their imagery need to implement workflow that helps to guarantee the authenticity of the process.
Everyone who looks at photographs—and that is all of us—needs to know that digital photographs are artifacts that can be constructed one pixel at a time (or using tools that operate on pixels in bulk). It has always been possible to manipulate photography, but with digital photography it is necessary, easy, and sometimes very hard to detect. (Of course, the fakery is not hard to detect with the Adnan Hajj photos.)
There's also a thin line between manipulating a news photograph in post-processing, and staging an image. There have long been charges that some of the most famous examples of war photography have been staged, going back to the heyday of silver halide photojournalism.
Skepticism is called for. The further implication is that the context of the photograph (and the person or organization vouching for it) has become increasingly important.
Wonderful Water Worlds
A good and bright morning in the garden, with the chance to photograph all these wonderful worlds of water.
Some of my water drop worlds are well defined with sunbursts, others look like stained glass, and still others are bright worlds that are more about sunlight than water.
The photo at the bottom of this series is part of the McClamp Bubble sequence, and shows my garden reversed and upside down in the water world!
Here's a link to my water drop photo set on Flickr!
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View this photograph larger.
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Golden Gate Sunset with Flare
From Indian Rock near my home in Berkeley, this view of the Golden Gate definitely has "flare!" Lens flare.
A Different Light
These two photos represent a different "take" on the water drop theme: like Different Signals they are more about the effects of light on the drops, and less about the worlds within drops.
View this photograph larger.
Different Signals
This water drop photo differs from most of my water drop images because it is an exercise in selective focus and relatively low depth-of-field. It was exposed at f/8 for 1/80 of a second, and a single drop on the spider web strand is apparently sharp. More typically with these photos I stop the lens as far down as it will go, and make a much longer exposure.
Here's more about my water drop photo techniques.
Stanislaus River Dawn
Julian and I went rafting on the Stanislaus River with his cousins David and Steven, Uncle Chris and Aunt Dejonghe (my nephews and in-laws). A good time was had by all.
In the early morning at the campsite by the put-in, there was a cool mist over the river (shown here). But later on in the day it was hot hot hot!
I've often thought that river trips are dream-like: the slow progression to putting-in, and the one-way trip with a logic all its own. Once you are on a river you do not know where it will take you, and most of the choices are made by the river.
My Favorite Worlds
If you've been reading my blog, you'll know that I've been photographing water drops. And that for me, each water drop is a world, as Blake put it, in a grain of sand. (Here's a fairly complete selection of my water drop photos on Flickr.)
The two photos in this story are among my favorites of my recent water drop worlds. Everything seems to come together in the photograph of a single drop above: sharp focus on the drop, a nice sunburst, and a nice inner world showing the white Scabiosa atropurnea ("Snow Maiden") that hosts the water drops and shows drops within the drop.
The photograph below shows a cosmos full of water drops, each caught by the thin filament of a spider's web, and on and on into an apparent infinity.
Both photographs were captured with the same gear, and roughly the same setup. That is, my wonderful Nikon D200, my stupendous Nikkor 200mm f/4 macro lens, a 36mm extension tube and a +4 diopter close-up filter, mirror lockup, and a remote trigger. The single drop (above) was exposed at f/36 for 0.2 of a second, and the multiple drops (below) at f/40 and 0.8 of a second (both ISO 100).
To digress for a second, the 200mm f/4 Nikkor macro is as heavy as big telephoto lens (which it kind of is at 300mm 35mm equivalence). One of the things about it that really makes my life easier is the built-in tripod collar. The tripod collar lets me shift the center of gravity forward on the tripod (by mounted the lens rather than the camera). It also lets me change the orientation of the photograph by loosening the screw that holds the collar in place and rotating the lens. Meaning that I don't have to move the camera at all. A big, expensive, special purpose lens. But well worth the price if you do much macro work.
View this photograph larger.
Golden Golden Gate Bridge
This is the final exposure from the other night on Marin headlands. Here's an earlier view looking towards the Golden Gate Bridge bridge (and from a position slightly closer to the bridge), and a moon-and-star-scape taken, well, thirty seconds or so before this exposure (but looking in the opposite direction).
I think that I like this view best of all my Golden Gate Bridge views because as Nadine put it on Flickr, the photo shows a bridge that is "TRULY the GOLDEN GATE Bridge." Yes, this bridge is golden.
In common with the other late evening (or nighttime) views, and indeed many of my landscapes, I post-processed this photo by exposing the RAW image several times and combining the different exposures. This process can feel a lot like combining photography with painting, since the amalgamation is often achieved by used the Photoshop brush tool on a layer mask.
It is emphatically not high dynamic range (HDR) photography, which stitches together multiple images with different exposures taken at the same time. I think I get more natural-looking results with multi-RAW processing than any HDR imagery I've seen. I'm also not quite sure why one needs the extra exposure range from many original images, since the RAW conversion itself gives you six stops of latitude.
These six stops range from -3 f/stops to + 3 f/stops, centered around the actual exposure. Bear in mind that f/stops are the denotation for the opening of the lens diaphragm, and are on a logarithmic scale. Each full f/stop lets in half the light of the f/stop that is next smaller. By the way, and somewhat counter intuitively, the smaller the f/stop number the larger the lens opening. So f/40 means that the lens is only open a little bit in its center, while f/2.0 probably means that the lens is open all the way (or almost all the way).
The 6 stop range means that from lightest to darkest with a RAW conversion the ratio is 1:1/2^6. (2^6 is notation for 2 to the 6th power.) Multiplying this out, 2^6 is 64, so in any RAW capture you have a 64X exposure range. This should really be enough for any exposure that doesn't have over-the-top burn out aspects, like direct digital sun captures, which often look like dripping hard-boiled eggs no matter what the exposure settings. Even in this successful direct-sun capture, the sun is basically highlighted out.
It's important in this time of a new and vital digital technology and craft not to lose sight of basics like how to expose photos, and the relationship of one f/stop to the next.
Starry Night
This is a photograph looking away from the Golden Gate Bridge out the Golden Gate towards the open ocean. On the right you can see Point Bonita. If you look hard in the larger version of this photo, you can see the Point Bonita light. On the left, there's a boat, Point Lobos and Land's End, and the ambient lights of the Sunset district of San Francisco.
I was photographing the Golden Gate Bridge after dark. I turned round, and saw this beautiful moonscape. I thought I might as well try to capture it, although you never know what you are going to get with these kinds of exposures. A key point: I used the menus on my Nikon D200 to turn on the long exposure compensation since this image was exposed for thirty seconds.
I like best the way the stars appear in the nighttime sky.
I processed the RAW original four times in Photoshop to come up with the version you see here. First, I created exposures for the sky and ocean. I added them as layers, and used a layer mask and a gradient to combine the two layers.
Next, I processed the RAW file a third time to expose properly for the moonlight reflected on the water. I combined this layer with what I had already done using a layer mask filled with black (hiding everything). I painted on the black layer mask with a white brush set to varying opacities to bring out the reflected moonlight. I used less opacity and flow towards the edges of the area I wanted to bring in, and more towards the center.
Finally, the moon itself needed some work. In fact, the moon was much brighter than anything else in the image. So I did a fourth RAW conversion to expose for the moon. This meant boosting the shadow slider, dropping the brightness slider, and lowering exposure as far as it would go. I then used the same layer mask painting technique as I used with the reflected moonlight, with concentric rings of greater opacity towards the center of moon.
While it was not trivial to shoot this image in the field, the main issues there were things like getting my tripod set up in the dark, not falling off a cliff, and so on. It's a fair statement that most of the intellectual effort with this photo took place in the post-processing.
Also true: what I "saw" when I took the photo was beautiful, but it did not "look like" my final image. A couple of reasons: the camera sensor picks up light spectrum that is invisible to the the human eye. And my post-processing resulted in an image with a greater range from light to dark than any conventional photograph could have rendered from the scene.
I went over to the Marin Headlands to photograph the Golden Gate Bridge at sunset. At first, with the D200 on my tripod, I used a polarizer and stopped the camera down as far as possible to get the car headlights to solidify.
As the lights of San Francisco, the Golden Gate Bridge, and the stars came out, my exposures grew longer and longer. From what I could tell on the LCD viewer, my images were starting to look a little murky and pixelated (I almost wrote "grainy," but I realized in time we don't have grain any more!).
So I reversed course, and opened the lens up wide. After all, with a fifteen second exposure, headlights will look like a solid line without making the exposure any longer. I also used the Nikon D200 menu to turn on the long exposure option. This reduces random pixelation within an image exposed for more than eight seconds at the expense of taking longer to save the image (for a while I wondered why the camera was flashing "JOB" at me) and of making the image file size larger.
Back home, on my computer, I realized that the bridge, its shadow, and the light it projected all approached convergence. As did the image I saw in my mind's eye when taking the picture and the digital photo I was viewing on the computer!


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Oct. 18, 2004
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The University of New Mexico seeks consecutive wins for the first time this season as San Diego State comes to town Saturday for UNM's 80th homecoming game. The Lobos and Aztecs kick off at 4:37 p.m., Mountain Time from University Stadium. The game will be televised live by SportsWest with local availability provided by KRQE-TV in Albuquerque. It's also part of the ESPN GamePlan package.
The Lobos improved to 3-4 overall and 1-2 in the Mountain West Conference with a 24-20 victory last week at UNLV, halting a two-game losing streak in the process. UNM trailed 17-7 five minutes into the second period. New Mexico is 3-4 after seven games for the sixth consecutive season. The past three years, however, UNM has played well enough in late October and November to become bowl eligible with invitations coming from the Las Vegas Bowl in 2002 and `03.
San Diego State is 2-4 in all games and 0-2 in the league after a tough 21-17 home loss to Colorado State. The Aztecs, who held CSU to 196 total yards, have dropped three in a row and are winless in three road games this season. SDSU has the same record as UNM did going into last week's tilt at UNLV.
Mountain West Conference road teams have a 6-4 record after 10 league games.
Both UNM and SDSU attempted to hold onto leads in the closing minutes of their respective games last week. The Lobos prevailed by causing their sixth turnover with a minute left in the 24-20 triumph at UNLV. San Diego State had the ball and a 17-14 lead over Colorado State with less than two minutes remaining, but the Aztecs fumbled at their own 10-yard line, allowing the Rams to punch in the winning score with just 1:10 left.
A quick look at the stats shows a run-first Lobo team facing the league's top run-stopper in San Diego State. With QB Kole McKamey and TB DonTrell Moore healthy for the first time in four games, New Mexico is coming off a 284-yard rushing day at UNLV. UNM is now averaging 174.6 yards a game on the ground with Moore churning for 101.2 in six games. The Aztecs are allowing just 103 rushing yards a game to rank No. 17 nationallly. SDSU has been even better in two MWC games as Wyoming and Colorado State - both passing squads - were stifled to a combined 135 yards. UNM is last in the conference and 107th overall in total offense at 292.1 yards a game. San Diego State is allowing a stingy 325 yards a game, but only 230 in its first two MWC contests. The Aztecs are also among the nation's leaders in pass efficiency defense with a rating of 102.2. The Lobos' pass efficiency offense rating of 75.7 ranks 116th out of 117 schools.
On the other side of the ball, SDSU is averaging 405.2 yards of offense, including 273 yards a game through the air, 2nd in the league and 16th in the NCAA. All those yards have not been turned into points, though, as the Aztecs are averaging just 20.5 points a game and rank last in the loop in 3rd-down conversions at 28 percent (28-100). The Lobos are allowing 20.4 points and 347.9 total yards a game. Both teams have registered 18 sacks, trailing only BYU's 22.
After gaining six turnovers at UNLV, the Lobos now lead the conference and rank 17th in the nation in turnover margin at +1.0 for the year.
New Mexico has a 39-37-3 record in homecoming games since the first one was played in 1925. UNM has been successful of late, winning five straight and 9 of 11 since 1993. San Diego State has been the homecoming opponent twice and has spoiled the festivities both times: 35-7 in 1979 and 49-21 in 1992.
Saturday's game pits head coaches who are serving their alma maters. Rocky Long was a three-year starter at quarterback and graduated from New Mexico in 1974. Tom Craft received his diploma from San Diego State in 1977.
GAME SPONORS / PROMOTIONS - Game sponsors include Bank of Albuquerque, COMCAST, 107.9 Big Country and 94 Rock.
In addition to the normal homecoming coronation activities, there will be a postgame fireworks show. The first 1,200 fans will receive a Brian Urlacher bobblehead courtesy of Bank of Albuquerque, and the UNM men's and women's basketball teams will be recognized during the first quarter break.
COACH LONG SAYS - (on UNLV) -- "That was a game exactly like I thought it would be with all the momentum shifts. We caused a fumble at the end of the game that gave us the win. We have speed on defense and in the first half we were running past the toss sweep. In the second half we played it much better. That forced them to go to other things. Our defense did some things to get our offense moving. One of the key plays in the game was after the roughing the kicker penalty, Gabriel Fulbright got a pick in the end zone to keep the game close. Our offense did a much better job and I liked the way we mixed it up."
(on San Diego State) -- "They are in nearly the exact same situation as we were at this time last week: 2-4 overall, 0-2 in the league and coming off a tough loss. They're a talented team and I know they will come in here with a lot of energy. Utah certainly appears to be the best team in the league, but after that we are all very even. Most of the games have been decided by a touchdown or less. We all have a couple of players that can impact the game. As usual when teams are evenly matched, turnovers usually play a big part in the outcome."
LONG APPROACHING RECORD FOR GAMES COACHED - Head coach Rocky Long is in his seventh season at his alma mater and is now third on the school's all-time win list at 36-44.
In terms of total seasons, only Roy Johnson (11) and Bill Weeks (8) have been at UNM for more time than Long. However, with 80 games spent on the sidelines, Long will become the school's career leader in games coached when the Lobos visit BYU on Nov. 13. That will be Long's 83rd game at UNM, surpassing Weeks' total of 82 from 1960-67.
UNM VS. SAN DIEGO STATE - New Mexico and San Diego State meet for the 31st time. SDSU leads 20-10, although the Lobos have won 3 straight for the first time since the first three games of the series (1953-56). UNM has a 4-1 lead in MWC games, including last year's 30-7 victory at San Diego.
The Aztecs have a 10-4 lead in Albuquerque, including an 8-game winning streak from 1986-2000. SDSU has a 10-6 advantage in San Diego, however, UNM has won 4 in a row at Qualcomm Stadium after losing 7 straight between 1984-95.
The Lobos' 15-8 victory two years ago in Albuquerque snapped a six-game winning streak by the visiting team. Lobo LB Billy Strother knocked down a pass on 4th-and-2 from the Aztec 6 to secure the win.
The average margin of victory in the last six games is a mere 7 points, which includes UNM's 23-point win last year. The Lobos have held SDSU to averages of 11.8 points and 245 yards of offense in the last four games. However, UNM has not been much better against the Aztec defense, averaging only 267.4 yards in the past five contests.
Aztecs' secondary and special teams coach Fred Bleil was UNM's defensive coordinator under Dennis Franchione from 1992-95
LAST YEAR AT SAN DIEGO STATE - New Mexico tied a school record by intercepting five passes - three by Gabriel Fulbright in the end zone - and Billy Strother returned a blocked punt for a TD in the 30-7 triumph. The 23-point margin is the Lobos' largest in San Diego. Turnovers and special teams play led directly to 20 of UNM's points.
The Aztecs entered the Lobo red zone six times and came away with just one TD. The other results were three interceptions, a missed field and a turnover on downs.
San Diego State marched inside the Lobo 10 on its opening drive of the game, but missed a 23-yard FG. A Brandon Ratcliff interception put UNM in great shape at the SDSU 19 and DonTrell Moore scored five plays later from the 2 and a 7-0 lead.
The Aztecs got to the Lobo 6 on their next drive, but Fulbright ended the threat with his first interception on a slant route.
The first quarter stats showed the Lobos with one first down and just 23 yards of offense while the Aztecs produced seven first downs and 172 total yards.
In the second quarter, Hank Baskett blocked Seth Santoro's punt. Strother picked up the loose ball and scored from the 14 to give UNM a 14-0 lead. The Aztecs answered with their only score of the night, going 64 yards in 10 plays. The Lobos got a big lift right before halftime. With less than a minute remaining in the half, Ratcliff returned a pooch kickoff to the 44 then QB Casey Kelly connected with WR Dwight Counter on a 23-yard pass. That set up a 48-yard FG by K Wes Zunker to give UNM a 17-7 lead at the break. Statistically, SDSU had a huge advantage at halftime with 274 yards of total offense to UNM's 103. The Lobos only had three first downs in the first half.
UNM really put it away on the opening series of the second half, mounting a 73-yard drive that ended in Moore's 3-yard run. The key play was Moore's 45-yard run on a 2nd-and-24 from the Lobo 13. He looked to be stopped twice on the play, but kept churning. UNM added two more FGs by Zunker and forced four more turnovers.
After having the ball for just 10:19 of the first half, UNM controlled the clock for 19:50 after halftime. The Lobos generated 223 yards of offense in the third and fourth quarters, while holding SDSU to just 119.
The three interceptions by Fulbright are the most by a Lobo since Sharay Fields set the single-game record of four against New Mexico State in 1979. The only other Lobos with three picks in a game are Chuck Roberts vs. Montana in 1959, Eddie Stokes vs. Montana in 1963 and Jay Morrison vs. San Jose State in 1969. Fulbright also added a season-high six tackles.
UNM forced six turnovers (5 interceptions, 1 fumble) against San Diego State, the most since Hawaii lost six fumbles in 1994.
TWO YEARS AGO IN ALBUQUERQUE - Playing their third consecutive heart-stopper, the Lobos held off San Diego State 15-8. A safety with 3:22 left in the final period provided New Mexico with the eventual seven-point margin, but it was far from over. The Aztecs completed a 39-yard pass to the UNM 13 with just over one minute to go. An 11-yard completion on 3rd-and-14 advanced the ball to the 6. With the Aztecs out of timeouts and the game clock winding down, Adam Hall's final pass attempt was batted away by Lobo LB Billy Strother, preserving the victory with just seven seconds remaining.
With swirling winds gusting to more than 40 mph, both teams were unable to do much on offense. The normally potent Aztecs passing game was held to 153 yards, or 180 yards below their season average. SDSU finished with just 183 yards of total offense, however, UNM was not much better, gaining only 237.
San Diego State held an 8-7 lead until early in the fourth quarter. Following a sack and forced fumble by S Terrell Golden that was recovered by fellow S Brandon Ratcliff, the Lobos marched 64 yards in 10 plays, capped by RB DonTrell Moore's 1-yard plunge. The big plays on the drive were a 13-yard run by WR Adrian Boyd on 3rd-and-4 and a 25-yard screen pass from QB Casey Kelly to TE Bryan Penley that put UNM 1st-and-goal at the 3.
After a Tyler Gaus punt backed SDSU up to its own 6, Ratcliff and Strother combined to sack Hall in the end zone. The ball squirted out of the back of the end zone for the safety and a 15-8 advantage.
The Lobos beat San Diego State in Albuquerque for the first time since 1983. The Aztecs had won eight straight at University Stadium. It also marked the first time since 1995 that the road team did not win.
The Lobo defense was spectacular considering San Diego State started four drives inside UNM territory (36, 42, 38 and 46-yard lines) and got just two field goals in the process. UNM stopped the Aztecs three times on 4th down and limited SDSU to just 2 of 15 conversions on 3rd down.
AZTEC NOTES - San Diego State was 6-6 last year and tied for 4th in the MWC at 3-4. Head coach Tom Craft (San Diego State `77) is 12-19 in his third year at his alma mater. Craft is 0-2 against the Lobos.
Senior LB Kirk Morrison is a two-time all-conference honoree and defending MWC defensive player of the year. Recently named a semifinalist for the Butkus Award, Morrison was named the league's defensive player of the week in the 21-17 loss to Colorado State. He recorded 14 tackles including eight solo, as San Diego State limited the Rams to a season-low 196 yards of total offense. Morrison also had two tackles for loss, forced a fumble and recovered a fumble. He leads the MWC in tackles, averaging 10.3 a game.
Junior WR Jeff Webb leads the conference and is 8th nationally in receiving, averaging 7.3 receptions a game (43 catches in 6 games). Webb has caught at least one pass in his last 16 games and three or more in his last 11.
UNLV REVIEW - With the 24-20 win at UNLV, the Lobos have won 6 of their past 8 MWC road games and 8 of 11...they also avoided an 0-3 conference start for the first time since 1998, the last year of the WAC...UNM is now 2-3 against UNLV in Las Vegas, winning the past 2
After averaging 208 yards of offense in its previous two games, UNM finished with 376 yards, 194 in the first half...New Mexico grounded out 284 rushing yards and is now 18-3 under Rocky Long when rushing for more than 225 yards
Once again, the Lobo defense had a big second half, allowing just 3 points and 138 total yards, including 29 yards rushing...over the past 6 games opponents have averaged just 4.3 points (4 FGs, 2 TDs), 49.3 yards rushing and 137.3 total yards after halftime
The Lobos overcame a 17-10 halftime deficit to notch their first win in four tries this season when trailing after two quarters...UNM shut the door on its 24-17 third-quarter lead, however, winning for the 17th time in its last 18 games when leading after three quarters...the only loss in that span was 21-17 in this year's opener vs. Washington State (a 14-7 lead)
UNM forced 6 turnovers, recording 2 interceptions in the 1st half and recovering 4 fumbles in the 2nd half, while playing turnover-free itself...UNM scored 17 points following the Rebel errors...the 4 fumbles lost are the most by a Lobo opponent since San Diego State had 4 in the Lobos' 24-21 road victory in 1999...the 6 giveaways tie for the most turnovers by a UNM foe since Rocky Long became head coach in 1998...the Aztecs gave the ball away 6 times in the Lobos' 30-7 road win last year...UNM, meanwhile, did not have any errors for the first time in 10 games, since last year's 24-12 win over Air Force...the Lobos had 15 turnovers (10 int/5 fumbles) in the eight games in between...New Mexico is 27-9 under Rocky Long when committing fewer turnovers than its opponents and has won 10 of its last 11 when winning the turnover battle...the Lobos are 11-1 all-time under Long when it does not commit a turnover versus a 1-10 mark when it does not cause a turnover
Junior LB Mike Mohoric recorded 6 tackles, including a pair of sacks that caused fumbles recovered by the Lobos...his first hit on Rebels QB Shane Steichen came after UNLV had marched to the UNM 48 and the score tied at 17...redshirt freshman walk-on DE Stephen Hutchison pounced on the loose ball and the Lobos scored the eventual game-winning TD five plays later...Mohoric's second sack preserved the victory...trailing 24-20, UNLV moved from its own 6 to the Lobo 41 with just over a minute remaining...he jarred the ball loose from QB Kurt Nantkes and LB Fola Fashola covered it...UNM was able to run out the clock
Redshirt freshman WR Marcus Smith's 65-yard TD run in the third quarter was the longest rush by New Mexico in 12 games (Adrian Byrd 78-yard non-scoring rush last year at Utah) and the longest scoring jaunt since third-string QB Justin Millea went 73 yards for a score in the third quarter at UNLV in 2002...Smith was a standout tailback at Morse High School in San Diego before moving to receiver midway through the 2003 season...he also returned 2 kickoffs for 41 yards and had a tackle on a punt return
Junior CB Gabriel Fulbright recorded a pair of interceptions, the second multiple INT game of his career...he now has three on the season...Fulbright stepped in front of Rebel WR Earvin Johnson on the first UNLV drive of the game, which set up the Lobos' opening TD drive of 50 yards...he also grabbed a pass intended for Johnson in the endzone late in the 2nd quarter that prevented the Rebels from adding to their 17-7 lead...Fulbright had a career-high 3 interceptions in a 30-7 UNM victory at San Diego State last year...four of his seven career INTs have come in the endzone
Junior WR Anthony Carter's 34-yard TD reception was the first of his career and just his third catch of the year...Carter's reception was the longest of the season by a Lobo wide receiver, other than Hank Baskett...Carter's 9-yard grab in the first quarter of the season opener vs. Washington State was the previous long
Sophomore QB Kole McKamey's 34-yard TD pass to Carter was the first passing score for the Lobos in six games, since McKamey hit Hank Baskett with a 7-yard pass against Texas Tech...UNM came into the game with an NCAA-low 1 TD pass as a team...McKamey, who did not travel to the Air Force game due to a concussion suffered against Utah on Oct. 1, completed 14 of 26 passes for 92 yards, 0 interceptions and the 1 TD...he also rushed 11 times for 24 yards...UNM is 3-2 this year when McKamey is heathly the entire game...he had to leave the Oregon State game in the second quarter with a concussion
Junior TB DonTrell Moore finished with 141 yards on 26 carries...it's his 2nd straight 100-yard effort, his 3rd of the season and 16th of his career to tie Winslow Oliver for the most in UNM history...Moore's 1st-quarter touchdown was just his second this season, and his first since scoring from 61 yards out in the 3rd quarter of the Lobos' season opener vs. Washington State...Moore had 21 TDs last year, one off the national lead...he now has 3,191 rushing yards and 34 touchdowns in his 32-game career
Senior S Josh Bazinet notched 8 tackles and his Mountain West Conference-leading 4th fumble recovery this season on a UNLV muffed punt to set up a UNM field goal in the 2nd quarter...Bazinet now has 6 fumble recoveries over the past two years
Senior K Wes Zunker had a string of 5 straight field goals snapped when his 3rd quarter kick was blocked...Zunker made a nice play, however, to prevent the Rebels from advancing the loose ball...UNLV was forced to punt on its ensuing possession...Zunker did convert a 32-yard FG, giving him 24 for his career, which ties Joe Bibbo for 6th place all-time at UNM...Zunker is now 6-9 on the year and 24-32 for his career...the 75% career accuracy ties Rick Walsh (18-24) for 2nd-best in the UNM record book...Zunker also sent two more kickoffs into the endzone, bringing his season touchback totals up to a career-high 8
UNM junior P Tyler Gaus was named MWC Special Teams player of the week after the UNLV game...Gaus punted 8 times for a 41.6-yard average and he dropped four balls inside the Rebels' 13-yard line...the four kicks came to rest at the 11, 3, 13 and 6-yard lines, respectively...his final boot was 53 yards and was downed at the 6, forcing the Rebels to travel 94 yards for a potential game-winning score...Gaus is averaging 40.6 yards on 49 kicks in 2004...18 of the boots have been downed inside the 20, while 10 have been fair caught...only 2 kicks have been touchbacks
SLOW STARTS, FAST FINISHES - That's been the story for Lobo football the past few seasons. As the leaves start to fall, so have the opponents. A look at UNM's recent record:
Year Start Finish (Regular Season Only) 2000 0-3 5-4 2001 2-4 4-1 2002 2-4 / 3-5 5-2 / 4-1 2003 1-3 7-2 2004 2-4 ???
TEAM NOTES TO DATE - UNM has outscored opponents 65-10 in the 3rd quarter and it's 51-0 in the Lobos' favor the past 5 games...the only teams to get on the board against the Lobos in the 3rd period are Washington State (1 TD) and Texas Tech (1 FG)
The Lobos have trailed by at least 10 points in the first half of all 3 MWC games: 21-7 to Utah, 21-0 at Air Force and 17-7 at UNLV...UNM also fell behind Oregon State 14-0 at the break
Attendance for Utah was a season-high 40,182, the 3rd-largest crowd in University Stadium history...through three home games, UNM is averaging 37,929 (113,788 total)...the school record for average attendance is 35,127 set last year
UNM has won nine straight games when it scores first...since the start of the 2001 season, the Lobos are 16-1 when getting on the scoreboard first...the only loss came at Utah State in 2002
The Lobos are 28-9 under Rocky Long when committing fewer turnovers in a game...they had won 10 straight before the loss to Utah...the Utes had three turnovers to UNM's two
The 21-17 loss to Washington State ended a 16-game UNM winning streak when it led after three quarters...the Lobos led the Cougars 14-7 going into the fourth quarter...the last loss had been to BYU in 2001, a game the Lobos led 13-10, but lost 24-20 to the 17th-ranked Cougars...must be something about playing the Cougars
It had been 12 years since New Mexico lost a game when leading by at least 10 points in the fourth quarter as it did against Washington State (17-7)...on Sept. 26, 1992, UNM had a 25-6 lead at Air Force only to fall 33-32 as the Falcons outscored the Lobos 27-7 in the final period
UNM and Washington State played to a scoreless first half, the first time the Lobos had been involved in that situation since Oct. 25, 1997, at Utah...the Utes eventually won that game 15-10
New Mexico has scored 4 touchdowns this season on defense or special teams
Wes Zunker's 43-yard FG as time expired gave the Lobos a gritty 27-24 victory over Texas Tech on Sept. 11, ending UNM's 10-game, 20-year losing skid against the Red Raiders...New Mexico had not beaten TTU since a 29-24 decision in Albuquerque on Sept. 22, 1984
The losses to Washington State and Oregon State pushed the Lobos' losing streak against Pac-10 teams to nine game
The Lobos' 38-3 win at New Mexico State was the largest victory margin in Las Cruces in 43 games, dating to 1905...it's the biggest road win since a 56-7 triumph at UTEP in 1972


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"Would you like to hear my story, Bella? It doesn't have a happy ending - but which of ours does? If we had happy endings, we'd all be under gravestones now."
I was born in Rochester, New York, in 1915; I had two younger brothers, a housewife for a mother, and my father worked at a bank. My father's job helped keep the family wealthy during the Great Depression. One day, my mother had me dress up to deliver my father's forgotten lunch to his job, in the hopes that the son of the bank's owner would take notice of me, and it worked. Royce King II sent roses to me and, after making a comment that my eyes were like violets, I began receiving them, too. Our relationship was solely based on physical attraction, as Royce was often too busy at the bank. We became engaged and shortly before the wedding, I visited my good friend Vera, who I envied for her baby boy. At one point, when Vera's husband kissed her, I finally noticed the lack of love in my relationship with Royce that was so obvious in Vera's. While walking home, shaken by my thoughts about my loveless relationship, I stumbled across my drunken fiancée and his equally drunk friends. Royce bragged about my beauty which eventually led to me, being brutally gang raped and beaten before being left in the street to die. I was found by Carlisle Cullen, the scent of blood having attracted him to the dying girl. He carried me to a room where he turned me in a vampire, worsening the pain I was already in. I awoke to the voices of the Cullens arguing with Carlisle about him saving me. Edward was unhappy with the idea that Carlisle had changed me in the hopes that I could be his mate. I was furious at Edward's rejection even despite my own lack of feelings for him as well. My vanity still needed feeding and I was surprised and hurt that Edward didn't seem attracted to me. Upon seeing my reflection, my unhappy mood increased with my now improved vampiric beauty. I soon avenged my death by killing Royce's friends. Having saved Royce for last, I donned a bridal gown for dramatic effect and found him locked in a windowless room with a thick, vault-like door guarded by two men. Killing the guards, I entered the room where I tortured Royce to death. Though I killed seven men, I was very careful to not spill even the smallest drop of their blood, knowing that I wouldn't be able to resist. After my transformation, I became a permanent member of the Cullen family. Carlisle had intended for Edward and I to be like he and Esme were, but Edward only loved me as a sister.
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Married Since:: Not Married Yet
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Pop music too loud and all sounds the same
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Join Date: Jun 2012
Location: Pleasantville NY USA
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Re: Pop music too loud and all sounds the same
Originally Posted by
con struct
But rock is not an offshoot of jazz. Rock is a direct descendant of southern guitar blues.
And jazz stopped being popular music when big bands began dying out and bebop became the new model.
Once pop music always pop music. Symphony and Opera is still pop in my book. Rock is not just the descendant of southern guitar blues. R&B (a type of bigband jazz with a heavier backbeat) is also one of it's direct predecessors as is C&W. Rock is an amalgamation of the pop music of the first half of the 20th century. in terms of song structure it owes a lot to C&W. in terms of rhythm and beat initially it bore much more resemblance to jazz. Listen to the drumming on early rock records. swing beat with snare on 2 and 4 while the guitar and piano hold down straight eighths giving a polyrhythmic feel. eventually things got evened out. straight eighths started holding sway. Also jazz is an offshoot of blues,ragtime, and marching music or was initially. regardless of how these genres are perceived now they all started as music for popular consumption and at their heart remain so.
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2015-2016 Audition Results
Welcome to the Family! We look forward to a great year with all of you!
Choir Executive Board 2015-2016
Congratulations to our Choir Executive Board for 2015-2016!
President: Jasmine Powell
Vice-President: Izzy Moore
Treasurer: Kali Winn
Historian: Faith Robertson
Librarian: Rachel Blugrind
The Program:
The Choral/Vocal Arts Department at San Juan Hills is dedicated to the development of each individual student's musical abilities and fueling each singer's personal passion for singing. The Choral/Vocal Arts Program does this by focusing instruction on healthy vocal technique, musicianship skills - including sight-reading and music theory, solo singing technique, and choral ensemble singing technique. Students are also given opportunities to audition and perform on stage as a solo artist with both classical and modern repertoire. The program is always growing and we are excited for the future for the department and each of these talented artists as they continue their musical education.
The Choral/Vocal Arts Program features four concerts in the 2014-2015 Academic Year with a Fall Concert, Winter Concert, Spring Concert, and a Pops Concert. The Pops Concert will also be featuring a live rock band to accompany the choirs and the soloists. We invite you, friends, family and anyone in the community to come and join us this year at all of our concerts! We promise you won't be disappointed!
Bowling & CPK Social Event!
The Choirs
Chamber Singers
The Chamber Singers are the most advanced choir in the Choral Department at San Juan Hills High School. This choir is an audition only choir composed mainly of upperclassmen with a musical background. The ensemble is geared towards those with a strong interest in singing and musicianship, whether it be solely here at San Juan Hills High School or in a future music career. The choir itself learns a great variety of music ranging over all time periods and genres, from early Baroque music to modern pop music, emphasizing all music styles as vital to the development of any musician. The Chamber Choir has rapidly become known as a heavily performing and educated choir and will continue to do so in the years to come.
Audtions for this group include:
- Singing a solo excerpt
- Vocalizing for test of range.
- Sight-reading a rhythmic/melodic excerpt.
Concert Choir
The Concert Choir is our wonderful women's ensemble on campus. There is no audition necessary. The student needs only the desire to sing. Similar to the Chamber Choir, they too sing a wide variety of music appropriate for singers of all ages and backgrounds.
Vocal Ensemble
Vocal Ensemble is a volunteer group made up of vocalists within and outside of the vocal department. Meeting exclusively during the singers' own free time, the group performs contemporary acappella repertoire for school functions and for choir concerts. The group often sees student lead rehearsals and/or sectionals run by the various officers in the group. The President of the Vocal Ensemble for the 2014-2015 year is Jasmine Powell.