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from sympy import symbols, Matrix, cos, sin, atan, sqrt, Rational
from sympy.core.sympify import sympify
from sympy.simplify.simplify import simplify
from sympy.solvers.solvers import solve
from sympy.physics.mechanics import dynamicsymbols, ReferenceFrame, Point,\
dot, cross, inertia, KanesMethod, Particle, RigidBody, Lagrangian,\
LagrangesMethod
from sympy.testing.pytest import slow
@slow
def test_linearize_rolling_disc_kane():
# Symbols for time and constant parameters
t, r, m, g, v = symbols('t r m g v')
# Configuration variables and their time derivatives
q1, q2, q3, q4, q5, q6 = q = dynamicsymbols('q1:7')
q1d, q2d, q3d, q4d, q5d, q6d = qd = [qi.diff(t) for qi in q]
# Generalized speeds and their time derivatives
u = dynamicsymbols('u:6')
u1, u2, u3, u4, u5, u6 = u = dynamicsymbols('u1:7')
u1d, u2d, u3d, u4d, u5d, u6d = [ui.diff(t) for ui in u]
# Reference frames
N = ReferenceFrame('N') # Inertial frame
NO = Point('NO') # Inertial origin
A = N.orientnew('A', 'Axis', [q1, N.z]) # Yaw intermediate frame
B = A.orientnew('B', 'Axis', [q2, A.x]) # Lean intermediate frame
C = B.orientnew('C', 'Axis', [q3, B.y]) # Disc fixed frame
CO = NO.locatenew('CO', q4*N.x + q5*N.y + q6*N.z) # Disc center
# Disc angular velocity in N expressed using time derivatives of coordinates
w_c_n_qd = C.ang_vel_in(N)
w_b_n_qd = B.ang_vel_in(N)
# Inertial angular velocity and angular acceleration of disc fixed frame
C.set_ang_vel(N, u1*B.x + u2*B.y + u3*B.z)
# Disc center velocity in N expressed using time derivatives of coordinates
v_co_n_qd = CO.pos_from(NO).dt(N)
# Disc center velocity in N expressed using generalized speeds
CO.set_vel(N, u4*C.x + u5*C.y + u6*C.z)
# Disc Ground Contact Point
P = CO.locatenew('P', r*B.z)
P.v2pt_theory(CO, N, C)
# Configuration constraint
f_c = Matrix([q6 - dot(CO.pos_from(P), N.z)])
# Velocity level constraints
f_v = Matrix([dot(P.vel(N), uv) for uv in C])
# Kinematic differential equations
kindiffs = Matrix([dot(w_c_n_qd - C.ang_vel_in(N), uv) for uv in B] +
[dot(v_co_n_qd - CO.vel(N), uv) for uv in N])
qdots = solve(kindiffs, qd)
# Set angular velocity of remaining frames
B.set_ang_vel(N, w_b_n_qd.subs(qdots))
C.set_ang_acc(N, C.ang_vel_in(N).dt(B) + cross(B.ang_vel_in(N), C.ang_vel_in(N)))
# Active forces
F_CO = m*g*A.z
# Create inertia dyadic of disc C about point CO
I = (m * r**2) / 4
J = (m * r**2) / 2
I_C_CO = inertia(C, I, J, I)
Disc = RigidBody('Disc', CO, C, m, (I_C_CO, CO))
BL = [Disc]
FL = [(CO, F_CO)]
KM = KanesMethod(N, [q1, q2, q3, q4, q5], [u1, u2, u3], kd_eqs=kindiffs,
q_dependent=[q6], configuration_constraints=f_c,
u_dependent=[u4, u5, u6], velocity_constraints=f_v)
(fr, fr_star) = KM.kanes_equations(BL, FL)
# Test generalized form equations
linearizer = KM.to_linearizer()
assert linearizer.f_c == f_c
assert linearizer.f_v == f_v
assert linearizer.f_a == f_v.diff(t).subs(KM.kindiffdict())
sol = solve(linearizer.f_0 + linearizer.f_1, qd)
for qi in qdots.keys():
assert sol[qi] == qdots[qi]
assert simplify(linearizer.f_2 + linearizer.f_3 - fr - fr_star) == Matrix([0, 0, 0])
# Perform the linearization
# Precomputed operating point
q_op = {q6: -r*cos(q2)}
u_op = {u1: 0,
u2: sin(q2)*q1d + q3d,
u3: cos(q2)*q1d,
u4: -r*(sin(q2)*q1d + q3d)*cos(q3),
u5: 0,
u6: -r*(sin(q2)*q1d + q3d)*sin(q3)}
qd_op = {q2d: 0,
q4d: -r*(sin(q2)*q1d + q3d)*cos(q1),
q5d: -r*(sin(q2)*q1d + q3d)*sin(q1),
q6d: 0}
ud_op = {u1d: 4*g*sin(q2)/(5*r) + sin(2*q2)*q1d**2/2 + 6*cos(q2)*q1d*q3d/5,
u2d: 0,
u3d: 0,
u4d: r*(sin(q2)*sin(q3)*q1d*q3d + sin(q3)*q3d**2),
u5d: r*(4*g*sin(q2)/(5*r) + sin(2*q2)*q1d**2/2 + 6*cos(q2)*q1d*q3d/5),
u6d: -r*(sin(q2)*cos(q3)*q1d*q3d + cos(q3)*q3d**2)}
A, B = linearizer.linearize(op_point=[q_op, u_op, qd_op, ud_op], A_and_B=True, simplify=True)
upright_nominal = {q1d: 0, q2: 0, m: 1, r: 1, g: 1}
# Precomputed solution
A_sol = Matrix([[0, 0, 0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 1, 0],
[sin(q1)*q3d, 0, 0, 0, 0, -sin(q1), -cos(q1), 0],
[-cos(q1)*q3d, 0, 0, 0, 0, cos(q1), -sin(q1), 0],
[0, Rational(4, 5), 0, 0, 0, 0, 0, 6*q3d/5],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, -2*q3d, 0, 0]])
B_sol = Matrix([])
# Check that linearization is correct
assert A.subs(upright_nominal) == A_sol
assert B.subs(upright_nominal) == B_sol
# Check eigenvalues at critical speed are all zero:
assert sympify(A.subs(upright_nominal).subs(q3d, 1/sqrt(3))).eigenvals() == {0: 8}
# Check whether alternative solvers work
# symengine doesn't support method='GJ'
linearizer = KM.to_linearizer(linear_solver='GJ')
A, B = linearizer.linearize(op_point=[q_op, u_op, qd_op, ud_op],
A_and_B=True, simplify=True)
assert A.subs(upright_nominal) == A_sol
assert B.subs(upright_nominal) == B_sol
def test_linearize_pendulum_kane_minimal():
q1 = dynamicsymbols('q1') # angle of pendulum
u1 = dynamicsymbols('u1') # Angular velocity
q1d = dynamicsymbols('q1', 1) # Angular velocity
L, m, t = symbols('L, m, t')
g = 9.8
# Compose world frame
N = ReferenceFrame('N')
pN = Point('N*')
pN.set_vel(N, 0)
# A.x is along the pendulum
A = N.orientnew('A', 'axis', [q1, N.z])
A.set_ang_vel(N, u1*N.z)
# Locate point P relative to the origin N*
P = pN.locatenew('P', L*A.x)
P.v2pt_theory(pN, N, A)
pP = Particle('pP', P, m)
# Create Kinematic Differential Equations
kde = Matrix([q1d - u1])
# Input the force resultant at P
R = m*g*N.x
# Solve for eom with kanes method
KM = KanesMethod(N, q_ind=[q1], u_ind=[u1], kd_eqs=kde)
(fr, frstar) = KM.kanes_equations([pP], [(P, R)])
# Linearize
A, B, inp_vec = KM.linearize(A_and_B=True, simplify=True)
assert A == Matrix([[0, 1], [-9.8*cos(q1)/L, 0]])
assert B == Matrix([])
def test_linearize_pendulum_kane_nonminimal():
# Create generalized coordinates and speeds for this non-minimal realization
# q1, q2 = N.x and N.y coordinates of pendulum
# u1, u2 = N.x and N.y velocities of pendulum
q1, q2 = dynamicsymbols('q1:3')
q1d, q2d = dynamicsymbols('q1:3', level=1)
u1, u2 = dynamicsymbols('u1:3')
u1d, u2d = dynamicsymbols('u1:3', level=1)
L, m, t = symbols('L, m, t')
g = 9.8
# Compose world frame
N = ReferenceFrame('N')
pN = Point('N*')
pN.set_vel(N, 0)
# A.x is along the pendulum
theta1 = atan(q2/q1)
A = N.orientnew('A', 'axis', [theta1, N.z])
# Locate the pendulum mass
P = pN.locatenew('P1', q1*N.x + q2*N.y)
pP = Particle('pP', P, m)
# Calculate the kinematic differential equations
kde = Matrix([q1d - u1,
q2d - u2])
dq_dict = solve(kde, [q1d, q2d])
# Set velocity of point P
P.set_vel(N, P.pos_from(pN).dt(N).subs(dq_dict))
# Configuration constraint is length of pendulum
f_c = Matrix([P.pos_from(pN).magnitude() - L])
# Velocity constraint is that the velocity in the A.x direction is
# always zero (the pendulum is never getting longer).
f_v = Matrix([P.vel(N).express(A).dot(A.x)])
f_v.simplify()
# Acceleration constraints is the time derivative of the velocity constraint
f_a = f_v.diff(t)
f_a.simplify()
# Input the force resultant at P
R = m*g*N.x
# Derive the equations of motion using the KanesMethod class.
KM = KanesMethod(N, q_ind=[q2], u_ind=[u2], q_dependent=[q1],
u_dependent=[u1], configuration_constraints=f_c,
velocity_constraints=f_v, acceleration_constraints=f_a, kd_eqs=kde)
(fr, frstar) = KM.kanes_equations([pP], [(P, R)])
# Set the operating point to be straight down, and non-moving
q_op = {q1: L, q2: 0}
u_op = {u1: 0, u2: 0}
ud_op = {u1d: 0, u2d: 0}
A, B, inp_vec = KM.linearize(op_point=[q_op, u_op, ud_op], A_and_B=True,
simplify=True)
assert A.expand() == Matrix([[0, 1], [-9.8/L, 0]])
assert B == Matrix([])
# symengine doesn't support method='GJ'
A, B, inp_vec = KM.linearize(op_point=[q_op, u_op, ud_op], A_and_B=True,
simplify=True, linear_solver='GJ')
assert A.expand() == Matrix([[0, 1], [-9.8/L, 0]])
assert B == Matrix([])
A, B, inp_vec = KM.linearize(op_point=[q_op, u_op, ud_op],
A_and_B=True,
simplify=True,
linear_solver=lambda A, b: A.LUsolve(b))
assert A.expand() == Matrix([[0, 1], [-9.8/L, 0]])
assert B == Matrix([])
def test_linearize_pendulum_lagrange_minimal():
q1 = dynamicsymbols('q1') # angle of pendulum
q1d = dynamicsymbols('q1', 1) # Angular velocity
L, m, t = symbols('L, m, t')
g = 9.8
# Compose world frame
N = ReferenceFrame('N')
pN = Point('N*')
pN.set_vel(N, 0)
# A.x is along the pendulum
A = N.orientnew('A', 'axis', [q1, N.z])
A.set_ang_vel(N, q1d*N.z)
# Locate point P relative to the origin N*
P = pN.locatenew('P', L*A.x)
P.v2pt_theory(pN, N, A)
pP = Particle('pP', P, m)
# Solve for eom with Lagranges method
Lag = Lagrangian(N, pP)
LM = LagrangesMethod(Lag, [q1], forcelist=[(P, m*g*N.x)], frame=N)
LM.form_lagranges_equations()
# Linearize
A, B, inp_vec = LM.linearize([q1], [q1d], A_and_B=True)
assert simplify(A) == Matrix([[0, 1], [-9.8*cos(q1)/L, 0]])
assert B == Matrix([])
# Check an alternative solver
A, B, inp_vec = LM.linearize([q1], [q1d], A_and_B=True, linear_solver='GJ')
assert simplify(A) == Matrix([[0, 1], [-9.8*cos(q1)/L, 0]])
assert B == Matrix([])
def test_linearize_pendulum_lagrange_nonminimal():
q1, q2 = dynamicsymbols('q1:3')
q1d, q2d = dynamicsymbols('q1:3', level=1)
L, m, t = symbols('L, m, t')
g = 9.8
# Compose World Frame
N = ReferenceFrame('N')
pN = Point('N*')
pN.set_vel(N, 0)
# A.x is along the pendulum
theta1 = atan(q2/q1)
A = N.orientnew('A', 'axis', [theta1, N.z])
# Create point P, the pendulum mass
P = pN.locatenew('P1', q1*N.x + q2*N.y)
P.set_vel(N, P.pos_from(pN).dt(N))
pP = Particle('pP', P, m)
# Constraint Equations
f_c = Matrix([q1**2 + q2**2 - L**2])
# Calculate the lagrangian, and form the equations of motion
Lag = Lagrangian(N, pP)
LM = LagrangesMethod(Lag, [q1, q2], hol_coneqs=f_c, forcelist=[(P, m*g*N.x)], frame=N)
LM.form_lagranges_equations()
# Compose operating point
op_point = {q1: L, q2: 0, q1d: 0, q2d: 0, q1d.diff(t): 0, q2d.diff(t): 0}
# Solve for multiplier operating point
lam_op = LM.solve_multipliers(op_point=op_point)
op_point.update(lam_op)
# Perform the Linearization
A, B, inp_vec = LM.linearize([q2], [q2d], [q1], [q1d],
op_point=op_point, A_and_B=True)
assert simplify(A) == Matrix([[0, 1], [-9.8/L, 0]])
assert B == Matrix([])
# Check if passing a function to linear_solver works
A, B, inp_vec = LM.linearize([q2], [q2d], [q1], [q1d], op_point=op_point,
A_and_B=True, linear_solver=lambda A, b:
A.LUsolve(b))
assert simplify(A) == Matrix([[0, 1], [-9.8/L, 0]])
assert B == Matrix([])
def test_linearize_rolling_disc_lagrange():
q1, q2, q3 = q = dynamicsymbols('q1 q2 q3')
q1d, q2d, q3d = qd = dynamicsymbols('q1 q2 q3', 1)
r, m, g = symbols('r m g')
N = ReferenceFrame('N')
Y = N.orientnew('Y', 'Axis', [q1, N.z])
L = Y.orientnew('L', 'Axis', [q2, Y.x])
R = L.orientnew('R', 'Axis', [q3, L.y])
C = Point('C')
C.set_vel(N, 0)
Dmc = C.locatenew('Dmc', r * L.z)
Dmc.v2pt_theory(C, N, R)
I = inertia(L, m / 4 * r**2, m / 2 * r**2, m / 4 * r**2)
BodyD = RigidBody('BodyD', Dmc, R, m, (I, Dmc))
BodyD.potential_energy = - m * g * r * cos(q2)
Lag = Lagrangian(N, BodyD)
l = LagrangesMethod(Lag, q)
l.form_lagranges_equations()
# Linearize about steady-state upright rolling
op_point = {q1: 0, q2: 0, q3: 0,
q1d: 0, q2d: 0,
q1d.diff(): 0, q2d.diff(): 0, q3d.diff(): 0}
A = l.linearize(q_ind=q, qd_ind=qd, op_point=op_point, A_and_B=True)[0]
sol = Matrix([[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, -6*q3d, 0],
[0, -4*g/(5*r), 0, 6*q3d/5, 0, 0],
[0, 0, 0, 0, 0, 0]])
assert A == sol
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