On robustness of suboptimal min-max model predictive control

With the hard computation of an exact solution to non-convex optimization problem in a limited time, we propose a suboptimal min-max model predictive control (MPC) scheme for nonlinear discrete-time systems subjected to constraints and disturbances. The idea of input-to-state stability (ISS) is introduced and a Lyapunov-like sufficient condition for ISS is presented. Based on this, we show that the suboptimal predictive controller obtained here holds back the disturbance robustly in the present of constraints on states and inputs. Key-Words: -Nonlinear predictive control; Suboptimal control; Input-to-state stability; Constraints * This work is supported by Natural Science Foundation of China under Grant 60674029 and the Specialized Research Fund for Doctoral Program of Higher Education of China under Grant 20050358044.