Linear Mismatched Model Based Offset-Free MPC for Nonlinear Constrained Systems With Both Stochastic and Deterministic Disturbances and Its Application to CSTR

This paper presents a linear mismatched model-based offset-free model-predictive control approach for nonlinear systems (also suits for mismatched linear systems) with both bounded stochastic and deterministic disturbances. By treating the objective function (using disturbance observer model) and the constraints (using mismatched predictive model) individually, offset-free tracking for piece-wise constant references in an expectation manner and constraints contentment has been achieved. A combined state and disturbance-affine feedback control law has been incorporated to achieve least conservativeness. Well-designed invariant set for tracking is used for convergence. An iterative computation procedure has been proposed to find the recursively feasible set, which ensures recursive feasibility. The final optimal control problem has been converted to a semidefinite programming problem that can be efficiently solved by existed solvers. The proposed method has been applied to a nonlinear continuously stirred tank reactor system, and the performance has been compared to several existing approaches.