控制理论(社会学)
约束(计算机辅助设计)
非线性系统
约束满足
李雅普诺夫函数
模型预测控制
计算机科学
传输(电信)
理论(学习稳定性)
联轴节(管道)
事件(粒子物理)
国家(计算机科学)
控制(管理)
数学
工程类
算法
物理
人工智能
机械工程
机器学习
电信
量子力学
概率逻辑
几何学
作者
Yu Kang,Tao Wang,Pengfei Li,Zhenyi Xu,Yun‐Bo Zhao
出处
期刊:IEEE transactions on cybernetics
[Institute of Electrical and Electronics Engineers]
日期:2023-09-01
卷期号:53 (9): 5572-5584
被引量:3
标识
DOI:10.1109/tcyb.2022.3159343
摘要
This article investigates the event-triggered distributed model predictive control (DMPC) for perturbed coupled nonlinear systems subject to state and control input constraints. A novel compound event-triggered DMPC strategy, including a compound triggering condition and a new constraint tightening approach, is developed. In this event-triggered strategy, two stability-related conditions are checked in a parallel manner, which relaxes the requirement of the decrease of the Lyapunov function. An open-loop prediction scheme to avoid periodic transmission is designed for the states in the terminal set. As a result, the number of triggering and transmission instants can be reduced significantly. Furthermore, the proposed constraint tightening approach solves the problem of the state constraint satisfaction, which is quite challenging due to the external disturbances and the mutual influences caused by dynamical coupling. Simulations are conducted at last to validate the effectiveness of the proposed algorithm.
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