A Stabilizing Model Predictive Control for Linear Systems with Input Saturation

Author

Li, Zhi-jun ; Tan, Wen ; Nian, Si-Cheng ; Liu, Ji-zhen

Author_Institution

Coll. of Electromech. Eng., North China Electr. Power Univ., Beijing

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

671

Lastpage

675

Abstract

A stabilizing model predictive control (MPC) strategy is proposed for linear systems with input saturation. A saturated linear feedback controller is selected as the local stabilizing controller. The terminal constraint set and terminal cost function can be computed by solving a corresponding semi-definite programming (SDP) problem. Then the control action is obtained by solving a second order cone programming (SOCP) problem on-line. Feasibility of SOCP problem implies the stability of the closed-loop system. Simulation shows that the proposed algorithm has a larger region of attraction than existed stabilizing MPC algorithms

Keywords

closed loop systems; control nonlinearities; control system synthesis; feedback; linear systems; mathematical programming; optimal control; predictive control; stability; closed-loop system stability; input saturation; linear system; saturated linear feedback controller; second order cone programming problem; semidefinite programming problem; stabilizing model predictive control strategy; terminal constraint set; terminal cost function; Closed loop systems; Control systems; Cost function; Industrial control; Linear systems; Machine learning; Power system modeling; Predictive control; Predictive models; Sampling methods; Stability; Input saturation; Model predictive control; Set invariance; Stability;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.258397

Filename

4028148