Model Predictive Control for Discrete-time Linear Systems with Finite-time Convergence

被引：0
|
作者：
Zhu, Bing [1 ,2 ]
Zuo, Zongyu [1 ,2 ]
Ding, Zhengtao [3 ]
机构：
[1] Beihang Univ, Seventh Res Div, Beijing 100191, Peoples R China
[2] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
[3] Univ Manchester, Dept Elect & Elect Engn, Sackville St Bldg, Manchester M13 9PL, Lancs, England
来源：
2020 59TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC) | 2020年
基金：
中国国家自然科学基金;
关键词：
Model predictive control; finite-time convergence; linear systems; discrete-time systems; OUTPUT DEADBEAT CONTROL; STABILIZATION; STABILITY; TRACKING;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a model predictive control (MPC) approach with finite-time convergence is proposed for constrained discrete-time linear systems. The proposed MPC is constructed based on a criterion of finite-time convergence for discrete-time linear systems, where its Lyapunov function decreases with a rate greater than that of exponential convergence. In the finite-time MPC, the cost function is designed particularly by using the proposed finite-time criterion. Recursive feasibility of optimization and stability of the closed-loop system can be proved within the classical MPC framework.
引用
收藏
页码：3531 / 3536
页数：6
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