Low-complexity stabilizing PWA controllers for linear systems with parametric uncertainties

被引:0
|
作者
Lu, Liang [1 ]
Kvasnica, Michal [2 ]
机构
[1] Zhejiang Univ, Ningbo Res Inst, Ningbo, Peoples R China
[2] Slovak Univ Technol Bratislava, Dept Informat Engn & Proc Control, Bratislava, Slovakia
来源
IFAC PAPERSONLINE | 2020年 / 53卷 / 02期
基金
中国国家自然科学基金;
关键词
Explicit model predictive control; Control Lyapunov function; Piecewise affine control; Parametric uncertainties; Linear programming; MODEL-PREDICTIVE CONTROL; TO-STATE STABILITY; LYAPUNOV FUNCTIONS; REDUCTION;
D O I
10.1016/j.ifacol.2020.12.569
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Explicit MPC often results in a large number of irregular partitions in the feasible region as the dimension of the system increases and the storage requirement for the control and region parameters often limit its applications. In this paper, we consider a class of discrete-time linear systems with polytopic parametric uncertainties and provide a robust control Lyapunov based synthesis method to obtain robust low-complexity PWA controllers on regular partitionings. By implementing a refinement procedure, we can fit the PWA feedback control law in each regular partitioning based on feasibility of linear programming problems, which preserves stability, constraint satisfaction, and certain performance requirement. Numerical examples will demonstrate the effectiveness of the approach. Copyright (C) 2020 The Authors.
引用
收藏
页码:7286 / 7291
页数:6
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