切换多智能体系统的全分布式比例一致性控制OA
Fully distributed scaled consensus for switched multi-agent systems
对切换多智能体系统的全分布式比例一致性控制问题进行了研究,其中多智能体系统(MAS)同时考虑了个体模型和通信网络的切换特性;控制输入受饱和约束限制;系统状态受比例特性影响;所采用的随机切换规则兼具马尔可夫切换与驻留时间切换的双重优势.由于个体模型与通信网络的随机切换特性、通信网络的全局信息未知、输入饱和约束以及个体状态间的比例特性所带来的难点,全分布式的比例一致性问题很难直接用现有方法解决.因此,设计了新的自适应比例一致性算法和李亚普诺夫函数,引入了代数黎卡提方程,并基于此给出了切换多智能体系统能实现几乎必然的全分布式指数比例一致性的条件.特别地,所获条件具有可行解且极易求解.最后,引入无人机集群验证了所提控制方案的有效性.
This paper investigates the fully distributed scaled consensus problem of switched multi-agent systems,in which the Multi-Agent System(MAS)involves both the switching characteristics of individual agent models and com-munication networks.Control inputs are subject to saturation constraints,and system states are affected by scaling properties.A stochastic switching law that integrates the advantages of Markov switching and dwell-time switching is employed.The difficulties caused by random switching of agent models and communication networks,unknown global information of the communication network,input saturation constraints,and scaling properties among individual states make the fully distributed scaled consensus problem difficult to be solved directly by existing approaches.Therefore,this paper designs a novel adaptive scaled consensus algorithm and a Lyapunov function,and introduces an algebraic Riccati equation.On this basis,the conditions are established under which the switched multi-agent system can achieve almost surely exponential scaled consensus in a fully distributed fashion.In particular,the obtained conditions admit feasible solutions and are very easy to solve.Finally,an unmanned aerial vehicle swarm is introduced to verify the effectiveness of the proposed control scheme.
孙亚平;王勇;袁爽;苏厚胜;妙锁霞;杨鑫松
四川大学 电子信息学院,成都 610065华中科技大学 人工智能与自动化学院,武汉 430074||华中科技大学 图像信息处理与智能控制教育部重点实验室,武汉 430074四川大学 电子信息学院,成都 610065华中科技大学 人工智能与自动化学院,武汉 430074||华中科技大学 图像信息处理与智能控制教育部重点实验室,武汉 430074江西水利电力大学 理学院,南昌 330099四川大学 电子信息学院,成都 610065
航空航天
多智能体系统一致性随机切换全分布式自适应控制输入饱和
multi-agent systemconsensusstochastic switchingfully distributedadaptive controlinput saturation
《航空学报》 2026 (z1)
91-100,10
国家重点研发计划(2025YFE0114800)国家自然科学基金(62303336,62561160100,62373262,62263024)特殊环境机器人技术四川省重点实验室开放基金资助(24kftk01) National Key R&D Program of China(2025YFE0114800)National Natural Science Foundation of China(62303336,62561160100,62373262,62263024)Fund of Robot Technology Used for Special Environment Key Laboratory of Sichuan Province(24kftk01)
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