Distributed Neural Network Control for Adaptive Synchronization of Uncertain Dynamical Multiagent Systems
Distributed Neural Network Control for Adaptive Synchronization of Uncertain Dynamical Multiagent Systems
复制标题
不确定动态多智能体系统自适应同步的分布式神经网络控制
DOI：
10.1109/tnnls.2013.2293499
复制
发表时间：
2014-08-01
影响因子：
10.4
通讯作者：
Sun, Gang
中科院分区：
文献类型：
--
作者：
Peng, Zhouhua;Wang, Dan;Sun, Gang
研究了具有非线性动力学的不确定多智能体系统的主从同步问题。提出了一种基于相邻代理状态信息的分布式自适应同步控制器。的控制设计开发的无向和有向通信拓扑结构，而不需要每个代理的准确模型。这个结果进一步扩展到输出反馈的情况下，提出了一个邻域观测器的相对输出信息的基础上相邻代理。然后，基于分布式的同步控制器的推导和参数依赖的Riccati不等式证明的稳定性。该设计对于非线性多智能体系统的观测器和控制器设计具有良好的解耦特性。对于这两种情况，所开发的控制器保证每个代理的状态与有界的残差的领导者的状态一致。两个示例验证了所提出的方法的有效性。
This paper addresses the leader-follower synchronization problem of uncertain dynamical multiagent systems with nonlinear dynamics. Distributed adaptive synchronization controllers are proposed based on the state information of neighboring agents. The control design is developed for both undirected and directed communication topologies without requiring the accurate model of each agent. This result is further extended to the output feedback case where a neighborhood observer is proposed based on relative output information of neighboring agents. Then, distributed observer-based synchronization controllers are derived and a parameter-dependent Riccati inequality is employed to prove the stability. This design has a favorable decouple property between the observer and the controller designs for nonlinear multiagent systems. For both cases, the developed controllers guarantee that the state of each agent synchronizes to that of the leader with bounded residual errors. Two illustrative examples validate the efficacy of the proposed methods.