Liu Guo-Ping
IEEE Trans Cybern. 2022 Feb;52(2):810-820. doi: 10.1109/TCYB.2020.2985043. Epub 2022 Feb 16.
This article studies the coordinated control problem of networked multiagent systems via distributed cloud computing. A distributed cloud predictive control scheme is proposed to achieve desired coordination control performance and compensate actively for communication delays between the cloud computing nodes and between the agents. This scheme includes the design of a multistep state predictor and optimization of control coordination. The multistep state predictor provides a novel way of predicting future immeasurable states of agents in a large horizontal length. The optimization of control coordination minimizes the distributed cost functions which are presented to measure the coordination between the agents so that the optimal design of the coordination controllers is simple with little computational increase for large-scale-networked multiagent systems. Further analysis derives the conditions of simultaneous stability and consensus of the closed-loop-networked multiagent systems using the distributed cloud predictive control scheme. The effectiveness of the proposed scheme is illustrated by an example.
本文研究了基于分布式云计算的网络化多智能体系统的协调控制问题。提出了一种分布式云预测控制方案,以实现期望的协调控制性能,并积极补偿云计算节点之间以及智能体之间的通信延迟。该方案包括多步状态预测器的设计和控制协调的优化。多步状态预测器提供了一种在较大水平长度上预测智能体未来不可测量状态的新方法。控制协调的优化使分布式成本函数最小化,这些成本函数用于衡量智能体之间的协调性,从而使协调控制器的最优设计对于大规模网络化多智能体系统而言简单且计算量增加很少。进一步的分析推导了使用分布式云预测控制方案的闭环网络化多智能体系统同时稳定和达成共识的条件。通过一个例子说明了所提方案的有效性。