摘要
基于分布式模型预测控制的多智能体系统跟踪一致是当前的研究热点,其中,作为研究难点的外部扰动处理和计算资源消耗降低尚缺少有效的解决方法.首先,论文提出了新的约束收缩方案,建立了新的分布式优化问题;然后,利用变时域思想设计了自适应事件触发机制,提出了多智能体系统跟踪一致的自适应事件触发分布式模型预测控制方法,有效解决了在受扰多智能体系统跟踪问题中约束不满足和计算资源消耗问题;最后通过多车辆系统仿真验证了所提方法的有效性.
The tracking consensus of multiagent systems based on distributed model predictive control(DMPC)is a current research hotspot.However,as a research difficulty,effective solutions to deal with external disturbances and reduce computational resource consumption are lacking.This paper proposes a new constraint tightening scheme and establishes a new distributed optimization problem.Moreover,an adaptive event-triggering mechanism is designed using the idea of variable prediction horizon,and an adaptive event-triggered DMPC approach for the tracking consensus of multiagent systems is proposed,effectively solving the problems of the unsatisfaction of constraints and computational resource consumption in the tracking consensus of multiagent systems.The effectiveness of the proposed approach is validated by a multivehicle system simulation.
作者
王涛
康宇
李鹏飞
WANG Tao;KANG Yu;LI PengFei(Department of Automation,University of Science and Technology of China,Hefei 230026.China;Institute of Advanced Technology,University of Science and Technology of China,Hefei 230088,China)
出处
《中国科学:技术科学》
EI
CSCD
北大核心
2023年第11期1885-1894,共10页
Scientia Sinica(Technologica)
基金
国家重点研究开发项目(编号:2018YFE0106800)
国家自然科学基金项目(批准号:62103394,61725304,62033012)
安徽重大专项科技项目(编号:201903a07020012)
中国博士后科学基金(编号:2020M682036)资助。