摘要
阐述在未知扰动下含有未知量的非线性多智能体系统控制问题。提出了一种分布式设计,可实现在加权有向图拓扑下的多智能体系统一致性跟踪控制。每个智能体由有未知量的严格反馈非线性系统建模,并包含外部干扰。通过backstepping技术和神经网络的方法,在只需要自己和相邻智能体之间的相对状态信息的情况下,为每个从智能体构造自适应分布式控制器。设计的控制器和自适应控制率可保证领航者与所有跟随器之间的跟踪误差收敛到原点的一个小邻域。运用Radial Basis Function(RBF)神经网络用于逼近未知的非线性函数,并设计了一个非线性扰动观测器用于估计未知的外部扰动。采用Nussbaum函数来处理模型中未知符号的参数,仿真结果验证了所提方法的有效性。
This paper focuses on the cooperative control problem for nonlinear multi-agent systems(MASs) with unknown disturbances. A distributed controller is designed for each agent system under a weighted directed graph topology. Each agent is modeled by a strict-feedback parameter system with uncertainties and unknown external disturbances. The time-varying leader node only gives commands to a small portion of the followers. By using the backstepping technique and neural networks method,an adaptive distributed controller for follower node is constructed, which only requires relative state information of its neighbors. The proposed controller and adaptive law can guarantee that the tracking error between follower and the leader convergences to a small neighborhood of the origin. Radial Basis Function(RBF) neural network is used to approximate the unknown uncertainties, and a nonlinear disturbance observer is constructed to estimate unknown external disturbances. Nussbaum function is used to handle parameters of unknown symbols in the model. Finally, a numerical example is proposed to demonstrate the effectiveness of the proposed approach.
作者
李段帅
王凯宁
彭钧敏
LI Duanshuai;WANG Kaining;PENG Junmin(College of Electrical and Informatica Engineering,Hunan University of Technology,Hunan 412007,China.)
出处
《电子技术（上海）》
2023年第1期70-73,共4页
Electronic Technology
