Min-max model predictive control for constrained nonlinear systems via multiple LPV embeddings

摘要：

A min-max model predictive control strategy for a class of constrained nonlinear systems,whose trajectories can be embedded within those of a bank of Linear Parameter Varying (LPV) models via an embedding scheme,is proposed.After getting the multiple LPV models to approximate the original nonlinear system dynamics,a parameter dependent Lyapunov function is introduced to obtain polyquadratically stable control laws,which can also guarantee the feasibility and stability of the original nonlinear system.The approach needs to solve a number of LMIs at each time instant,which can greatly reduce the computational burden compared with the traditional direct nonlinear predictive control strategies.Finally a simulation example illustrating the strategy is presented.

关键词： constrained nonlinear systems predictive control LPV embedding parameter dependent Lyapunov function.

作者: Min Zhao Shaoyuan Li

作者单位: Institute of Automation,Shanghai Jiao Tong University,Shanghai,China

会议类型: 国际会议

会议名称: International Conference on Modelling,Identification and Control(模拟、鉴定、控制国际会议)

会议地点: 上海

会议语种:英文

在线出版日期: 2008-06-29（万方平台首次上网日期，不代表论文的发表时间）