控制理论(社会学)
计算机科学
遏制(计算机编程)
控制器(灌溉)
事件(粒子物理)
控制(管理)
协议(科学)
芝诺悖论
分布式计算
控制工程
数学
工程类
人工智能
医学
物理
程序设计语言
几何学
农学
替代医学
病理
量子力学
生物
作者
Tao Xu,Yuqing Hao,Zhisheng Duan
出处
期刊:IEEE Transactions on Circuits and Systems I-regular Papers
[Institute of Electrical and Electronics Engineers]
日期:2020-04-02
卷期号:67 (6): 2078-2090
被引量:68
标识
DOI:10.1109/tcsi.2020.2971037
摘要
This paper focuses on the distributed containment control problems for multiple Euler-Lagrange systems with stationary/dynamic leaders over directed communication networks. When the leaders are stationary, a distributed event-triggered adaptive control law is presented, and three other update algorithms of the time-varying control gain are further designed for comparison. Then, a distributed event-triggered neural-network-based control protocol is developed when the dynamic leaders are considered. The aforementioned two control strategies can be implemented in fully distributed chattering-free manners since no global information and discontinuous items are employed. In addition, the requirement for relative velocity measurements are relaxed in controller design. The update frequency and energy consumption of the controlled systems are effectively reduced by applying the event-triggered mechanism. It is rigorously verified that the proposed event-triggered control protocols will not be updated infinitely in finite time, which indicates that the undesired Zeno behavior can be ruled out. Finally, the effectiveness of the theoretical results is illustrated by some simulation examples.
科研通智能强力驱动
Strongly Powered by AbleSci AI