Distributed Continuous-Time Optimization for Networked Lagrangian Systems with Time-Varying Cost Functions Under Fixed Graphs
Distributed Continuous-Time Optimization for Networked Lagrangian Systems with Time-Varying Cost Functions Under Fixed Graphs
复制标题
DOI：
10.23919/acc53348.2022.9867341
复制
发表时间：
2022-06
期刊：
影响因子：
--
通讯作者：
Yong Ding;H. Wang;W. Ren
中科院分区：
文献类型：
--
作者：
Yong Ding;H. Wang;W. Ren
本文研究了具有参数不确定性的网络拉格朗日系统的分布式时变优化问题。通常，在文献中，为了解决非线性系统的一些分布式控制问题，构造网络虚拟系统，并设计跟踪算法，使得代理的物理状态跟踪虚拟状态。值得指出的是，这种想法需要虚拟状态的交换，因此需要组之间的通信。此外，由于拉格朗日动力学和分布式时变优化问题的复杂性，存在显着的挑战。本文提出了一种分布式时变优化算法，实现零最优跟踪误差的网络拉格朗日代理没有通信的要求。所提出的算法背后的主要思想是构建一个动态系统，每个代理生成一个参考速度使用绝对和相对的物理状态测量与虚拟状态的交换所需的，并设计自适应控制器的拉格朗日系统，使物理状态能够跟踪参考速度，因此最优轨迹。该算法通过物理状态/测量引入参考系统和本地控制器之间的相互反馈，并且在通信不友好的环境中通过本地机载传感进行实施。
In this paper, the distributed time-varying optimization problem is addressed for networked Lagrangian systems with parametric uncertainties. Usually, in the literature, to address some distributed control problems for nonlinear systems, a networked virtual system is constructed, and a tracking algorithm is designed such that the agents’ physical states tracks the virtual states. It is worth pointing out that such an idea requires the exchange of the virtual states and hence necessitates communication among the group. In addition, due to the complexities of the Lagrangian dynamics and the distributed time-varying optimization problem, there exist significant challenges. This paper proposes a distributed time-varying optimization algorithm achieving zero optimum-tracking error for the networked Lagrangian agents without the communication requirement. The main idea behind the proposed algorithm is to construct a dynamic system for each agent to generate a reference velocity using absolute and relative physical state measurements with no exchange of virtual states needed, and to design adaptive controllers for Lagrangian systems such that the physical states are able to track the reference velocities and hence the optimal trajectory. The algorithm introduces mutual feedback between reference systems and local controllers via physical states/measurements and is amenable to implementation via local onboard sensing in a communication unfriendly environment.