论文标题
对通用图形的不确定领导者的自适应合作跟踪和参数估计
Adaptive Cooperative Tracking and Parameter Estimation of an Uncertain Leader over General Directed Graphs
论文作者
论文摘要
本文研究了具有不确定领导者的异质欧拉格朗格系统的合作跟踪问题。与大多数现有作品不同，引导节点的系统动态知识对于我们论文中的任何追随者节点都无法访问。分布式自适应观察者是针对所有追随者节点设计的，同时估计了领导者节点的状态和参数。观察者的设计不依赖引导节点的频率知识，并且显示估计错误呈指数收敛。此外，结果应用于一般的有向图，其中Laplacian矩阵的对称性无法保持。这是由于两个新开发的Lyapunov方程，它们仅取决于通信网络拓扑。有趣的是，使用这些lyapunov方程，可以将多代理系统的许多结果扩展到一般的有向图。最后，本文还通过为自适应观察者的参数收敛分析提供了一种主要工具来推动自适应控制系统的知识库。
This paper studies cooperative tracking problem of heterogeneous Euler-Lagrange systems with an uncertain leader. Different from most existing works, system dynamic knowledge of the leader node is unaccessible to any follower node in our paper. Distributed adaptive observers are designed for all follower nodes, simultaneously estimate the state and parameters of the leader node. The observer design does not rely on the frequency knowledge of the leader node, and the estimation errors are shown to converge to zero exponentially. Moreover, the results are applied to general directed graphs, where the symmetry of Laplacian matrix does not hold. This is due to two newly developed Lyapunov equations, which solely depend on communication network topologies. Interestingly, using these Lyapunov equations, many results of multi-agent systems over undirected graphs can be extended to general directed graphs. Finally, this paper also advances the knowledge base of adaptive control systems by providing a main tool in the analysis of parameter convergence for adaptive observers.
