赵广社, 张文慧, 高雷涛, 李国齐, 王鼎衡, 马凡波. 切换拓扑下时变非线性多智能体系统的一致性[J]. 信息与控制, 2020, 49(6): 641-648. DOI: 10.13976/j.cnki.xk.2020.0013
引用本文: 赵广社, 张文慧, 高雷涛, 李国齐, 王鼎衡, 马凡波. 切换拓扑下时变非线性多智能体系统的一致性[J]. 信息与控制, 2020, 49(6): 641-648. DOI: 10.13976/j.cnki.xk.2020.0013
ZHAO Guangshe, ZHANG Wenhui, GAO Leitao, LI Guoqi, WANG Dingheng, MA Fanbo. Consensus of Time-varying Nonlinear Multi-agent Systems under Switching Topologies[J]. INFORMATION AND CONTROL, 2020, 49(6): 641-648. DOI: 10.13976/j.cnki.xk.2020.0013
Citation: ZHAO Guangshe, ZHANG Wenhui, GAO Leitao, LI Guoqi, WANG Dingheng, MA Fanbo. Consensus of Time-varying Nonlinear Multi-agent Systems under Switching Topologies[J]. INFORMATION AND CONTROL, 2020, 49(6): 641-648. DOI: 10.13976/j.cnki.xk.2020.0013

切换拓扑下时变非线性多智能体系统的一致性

Consensus of Time-varying Nonlinear Multi-agent Systems under Switching Topologies

  • 摘要: 为了解决联合切换拓扑是任意有向网络结构的马尔可夫切换拓扑下多智能体系统一致性的问题,提出了一种对任意网络结构进行的构造方法,针对构造后的网络,设计了一种一致性协议,研究了时变非线性多智能体系统的“领导-跟随”一致性问题.首先,通过引入一个虚拟领导者节点与联合切换拓扑中最少数量的领导者连接,对任意有向网络结构进行构造,使所构造的网络拓扑包含有向生成树;其次,设计了具有动态增益的一致性协议,并引入一致性误差和状态变换,将系统的一致性问题转化为时变参数的设计问题;进一步,基于李亚普诺夫稳定性理论,分析了马尔可夫切换拓扑下时变非线性多智能体系统稳定性;最后,仿真示例说明了理论结果的有效性.

     

    Abstract: To solve the consensus problem associated with multi-agent systems under Markovian switching topologies in which the union of switching topologies is an arbitrary network structure, we propose a construction method for any network structure. We also design a consensus protocol for the constructed network to solve the problem of leader-follower consensus for time-varying nonlinear multi-agent systems. First, by introducing a virtual leader node that connects with the minimum number of leaders in the union of switching topologies, we construct an arbitrary network structure so that the constructed network topology includes a directed spanning tree. Next, we design a consensus protocol with dynamic gain, and introduce consensus errors and state transitions to transform the system consensus problem into a design based on time-varying parameters. Based on Lyapunov's stability theory, we analyze the stability of time-varying nonlinear multi-agent systems under Markovian switching topologies. The results of simulation examples demonstrate the validity of the theoretical results.

     

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