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Distributed adaptive iterative learning control for the consensus tracking of heterogeneous nonlinear multi-agent systems
Transactions of the Institute of Measurement and Control ( IF 1.7 ) Pub Date : 2020-05-05 , DOI: 10.1177/0142331220911833
Xiongfeng Deng 1 , Xiuxia Sun 2
Affiliation  

This paper addresses the consensus tracking problem of leader-following heterogeneous multi-agent systems with iterative learning control. The model of heterogeneous multi-agent systems consists of first-order and second-order nonlinear dynamics. It is assumed that only a portion of following agents can receive the leader’s information. The radial basis function neural network is introduced to deal with the nonlinear terms of following agents. Then, the distributed adaptive iterative learning control protocols with neural network are designed for following agents with different dynamics. Meanwhile, the adaptive update control laws for the time-varying parameters are proposed. Theoretical analysis shows that the consensus tracking problem of the given multi-agent systems can be guaranteed on the time domain and iterative domain. Finally, the validity of theoretical results is verified by a simulation example.

中文翻译:

用于异构非线性多智能体系统一致性跟踪的分布式自适应迭代学习控制

本文解决了具有迭代学习控制的领导者跟随异构多智能体系统的共识跟踪问题。异构多智能体系统模型由一阶和二阶非线性动力学组成。假设只有一部分跟随代理可以接收到领导者的信息。引入径向基函数神经网络来处理跟随代理的非线性项。然后,设计了具有神经网络的分布式自适应迭代学习控制协议,用于跟踪具有不同动态的代理。同时,提出了时变参数的自适应更新控制律。理论分析表明,给定的多智能体系统的一致性跟踪问题可以在时域和迭代域上得到保证。最后,
更新日期:2020-05-05
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