摘要
本文研究了一类带输入约束和状态约束的线性多智能体系统一致性问题.为解决智能体间通信及控制器更新频繁的问题,本文结合动态事件触发机制和模型预测控制原理,设计了动态事件触发的双模预测控制策略.在该控制策略作用下,多智能体系统在满足约束条件时能够以指数收敛速度实现一致性,且算法的可行性和系统的稳定性均得以保证.同时,连续两个触发时刻之间存在最小触发时间间隔,芝诺现象被排除.最后,针对需要连续检验事件触发条件的问题,本文设计了非周期、非持久的自适应触发条件验证方法,进一步节约了计算资源,数值仿真实验表明本文所提方法的有效性.
In this paper,a consensus problem is studied for a group of linear agents with input constraints and state constraints.To address the problem of frequent communication between agents and regular update of information between decentralized controllers,the dynamic event-triggered control mechanism(DETC)and the dual-mode model predictive control principles(MPC)are integrated to formulate the distributed consensus control protocols,i.e.DETC-MPC.Under this control strategy,the agents can meet the constraints on system states and inputs when they are steered to reach consensus with an exponential convergence rate.Both of the feasibility of local MPC optimization and the stability of resultant closed-loop system are guaranteed.Meanwhile,a minimum inter-event time is ensured between any two consecutive triggering instants and thus no agent exhibits Zeno behavior.To avoid continuous verification of event-triggering condition,a non-periodic and non-persistent method is designed to check triggering conditions.The numerical simulation shows the effectiveness of the proposed DETC-MPC.
作者
高翔宇
付东飞
孟浩飞
张玲
GAO Xiang-yu;FU Dong-fei;MENG Hao-fei;ZHANG Ling(College of Engineering,Ocean University of China,Qingdao Shandong 266404,China;College of Automation,Southeast University,Nanjing Jiangsu 210018,China)
出处
《控制理论与应用》
北大核心
2025年第12期2398-2408,共11页
Control Theory & Applications
基金
山东省自然科学基金项目(ZR2022MF280)
国家自然科学基金面上项目(62373106,52371355)资助。
关键词
多智能体系统
一致性
动态事件触发
模型预测控制
自适应算法
multi-agent systems
consensus
dynamic event triggering
model predictive control
adaptive algorithm
