Robust Contractive Economic MPC for Nonlinear Systems with Additive Disturbance

This article presents two novel robust contractive economic model predictive control (EMPC) algorithms with guaranteed input-to-state stability for nonlinear disturbed systems. Specifically, the first one adopts the non-quadratic economic objective function and implements the control sequence in block fashion, i.e., re-optimizing after all N control laws being applied. The second one takes receding horizon optimization strategy and only apply the first element in control sequence at each step. By appropriately chosen the contraction rate in contractive constraint, the closed-loop system under each control algorithm is proven to be input-to-state stable. In order to illustrate the efficiency of proposed algorithms, a disturbed CSTR model is utilized.