1. A method for optimising a process for a system having a steady-state objective function P(z ∞ )comprising: producing a minimisation of said steady-state objective function P(z ∞ ) using a computer wherein said minimisation is subject to a set of constraints wherein z min ≦Z ∞ ≦Z max and wherein values of a state vector, z, at different points in time are related via a model expressed in a dynamic open equation format Q(z ∞ , z k , z k-1 , z k-2 ,. .. , z k-n )=0, where z ∞ is a predicted final value of the state vector, z, and z k , z k-1 , z k-2 ,. .. , z k-n are current and previous values of the state vector, z; using said minimisation of said steady-state objective function P(z ∞ ) to control said process via said computer; wherein said steady-state objective function, P(z ∞ ), is expressed as the sum of a set of second order polynomials, P=A·z ∞ +(z ∞ −z tgt ) T ·B·(z ∞ −z tgt ), wherein: A is a vector of constants (LP coefficients); B is a diagonal matrix of constants (QP coefficients); and Z tgt is a vector of so called ideal resting values for state vector elements.