Quasi-min–max MPC for constrained nonlinear systems with guaranteed input-to-state stability

• DOI: 10.1016/j.jfranklin.2014.03.006
• Publication Date: 2014-04-04T02:17:22Z
• Authors: De-Feng He; Hua Huang; Qiu-Xia Chen
• Keywords: 0209 industrial biotechnology; 02 engineering and technology

Abstract This paper presents a robust quasi-min–max model predictive control algorithm for a class of nonlinear systems described by linear parameter varying (LPV) systems subject to input constraints and unknown but bounded disturbances. The proposed control algorithm solves a semi-definite programming problem that explicitly incorporates a finite horizon cost function and linear matrix inequalities (LMI) constraints. For the purpose of the recursive feasibility of the optimization, the dual-mode approach is implied. Input-to-state stability (ISS) and quasi-min–max MPC are combined to achieve the closed-loop ISS of the controller with respect to the disturbance in LMI paradigm. Two examples of continuous stirred tank reactor (CSTR) and couple-mass-spring system are used to demonstrate the effectiveness of the proposed results.