摘要
Aiming at a class of nonlinear systems with multiple equilibrium points, we present a dual-mode model predictive control algorithm with extended terminal constraint set combined with control invariant set and gain schedule. Local LQR control laws and the corresponding maximum control invariant sets can be designed for finite equilibrium points. It is guaranteed that control invariant sets are overlapped each other. The union of the control invariant sets is treated as the terminal constraint set of predictive control. The feasibility and stability of the novel dual-mode model predictive control are investigated with both variable and fixed horizon. Because of the introduction of extended terminal constrained set, the feasibility of optimization can be guaranteed with short prediction horizon. In this way, the size of the optimization problem is reduced so it is computationally efficient. Finally, a simulation example illustrating the algorithm is presented.
Aiming at a class of nonlinear systems with multiple equilibrium points, we present a dual-mode model predictive control algorithm with extended terminal constraint set combined with control invariant set and gain schedule. Local LQR control laws and the corresponding maximum control invariant sets can be designed for finite equilibrium points. It is guaranteed that control invariant sets are overlapped each other. The union of the control invariant sets is treated as the terminal constraint set of predictive control. The feasibility and stability of the novel dual-mode model predictive control arc investigated with both variable and fixed horizon. Because of the introduction of extended terminal constrained set, the feasibility of optimization can be guaranteed with short prediction horizon. In this way, the size of the optimization problem is reduced so it is computationally efficient. Finally, a simulation example illustrating the algorithm is presented.
出处
《自动化学报》
EI
CSCD
北大核心
2006年第1期21-27,共7页
Acta Automatica Sinica
基金
Supported by National Natural Science Foundation of P. R. China (60474051, 60534020)Development Program of Shanghai Science and Technology Department (04DZ11008)the Program for New Century Excellent Talents in Universities of P. R. China (NCET)
关键词
不变量集
非线性模型
预先控制
非线性约束系统
增益表
Invariant set, nonlinear model predictive control, constrained nonlinear systems, gain schedule
作者简介
ZOU Tao Received his Ph.D. degree from Shanghai Jiaotong University in 2005, and now he is a postdoctor at the same university. His research interests include optimal control of complex systems. （E-mail： syli@sjtu.cdu.cn）
LI Shao-Yuan Professor in the Department of Automation at Shanghai Jiaotong University. His research interests include model predictive control, fuzzy systems, and intelligent systems.
DING Bao-Cang Received his Ph.D. degree from Shanghai Jiaotong University in 2003, and now he is an associate professor in Hebei University of Technology. His research interests include fuzzy systems, chemical process control, and predictive control.
