Event-triggered robust model predictive control with stochastic event verification?

被引:7
|
作者
Deng, Li [1 ]
Shu, Zhan [1 ]
Chen, Tongwen [1 ]
机构
[1] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G 1H9, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Event-triggered control; Robust MPC; Stochastic triggering; Markov chains; Transition probability design; LINEAR-SYSTEMS; STABILITY; POLICY;
D O I
10.1016/j.automatica.2022.110638
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper is concerned with event-triggered robust model predictive control (MPC) for linear discrete -time systems with bounded disturbances. Based on the ergodicity of a purposely designed Markov chain, a stochastic triggering scheme involving a prescribed triggering function, an updating law for the transition probabilities of the Markov chain, and a checking function is proposed to achieve aperiodic and non-persistent event verification and enlarge the inter-execution time. Both tube-based MPC and linear matrix inequality-based (LMI-based) MPC are considered, and they show complementary merits with such a stochastic triggering scheme. Under mild conditions, recursive feasibility and closed-loop robust stability of both approaches are guaranteed theoretically. Simulation results are provided to show the effectiveness and merits of the proposed approaches.(c) 2022 Elsevier Ltd. All rights reserved.
引用
收藏
页数:11
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