Robust model predictive control for uncertain step response

The design of robust model predictive control for handling bounded uncertainties in step response of unconstrained MIMO processes is considered. The control law is obtained by minimizing an upper bound of the objective function and it consists of an optimal state feedback gain and a robust state observer. The separation principle is found to be applicable between the state feedback gain and the robust state observer. Simulation results show that the proposed algorithm can provide an improved handling of the uncertainty in step response as compared with a nominal MPC algorithm.