控制理论(社会学)
李普希茨连续性
模型预测控制
计算机科学
李雅普诺夫函数
补偿(心理学)
有界函数
多智能体系统
非线性系统
事件(粒子物理)
理论(学习稳定性)
控制(管理)
数学
心理学
数学分析
物理
量子力学
人工智能
机器学习
精神分析
作者
Mengzhi Wang,Chengcheng Zhao,Jinhui Xia,Jian Sun
出处
期刊:IEEE Transactions on Industrial Informatics
[Institute of Electrical and Electronics Engineers]
日期:2023-02-23
卷期号:19 (11): 11216-11228
被引量:6
标识
DOI:10.1109/tii.2023.3245189
摘要
This article investigates the problem of event-triggered distributed model predictive control (DMPC) for continuous-time nonlinear multiagent systems (MASs) subject to bounded disturbances, input and communication delays simultaneously. The compensation schemes for input and communication delays are proposed, respectively. A new optimal control problem (OCP) to achieve consensus among all agents is formulated under the proposed delay compensation schemes. To alleviate the communication burden and sensing cost, a novel input delay-related periodic event-triggering condition is proposed based on the state error to determine when to calculate the new control input. Sufficient condition guaranteeing the feasibility of the OCP is achieved with the proposed event-triggered control scheme. In stability analysis, a novel time-varying Lyapunov function is constructed, and the input-to-state practical stability of the MASs is derived by using the quasi-Lipschitz continuous property of the Lyapunov function. Numerical results related to vehicle platooning demonstrate the effectiveness of the proposed event-triggered DMPC.
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