Event-triggered distributed optimization for model-free multi-agent systems  

作　　者：Shanshan ZHENG Shuai LIU Licheng WANG 

机构地区：[1]College of Science,University of Shanghai for Science and Technology,Shanghai,200093,China [2]College of Automation Engineering,Shanghai University of Electric Power,Shanghai,200090,China

出　　处：《Frontiers of Information Technology & Electronic Engineering》2024年第2期214-224,共11页信息与电子工程前沿（英文版）

基　　金：Project supported by the National Natural Science Foundation of China(No.62003213)。

摘　　要：In this paper,the distributed optimization problem is investigated for a class of general nonlinear model-free multi-agent systems.The dynamical model of each agent is unknown and only the input/output data are available.A model-free adaptive control method is employed,by which the original unknown nonlinear system is equivalently converted into a dynamic linearized model.An event-triggered consensus scheme is developed to guarantee that the consensus error of the outputs of all agents is convergent.Then,by means of the distributed gradient descent method,a novel event-triggered model-free adaptive distributed optimization algorithm is put forward.Sufficient conditions are established to ensure the consensus and optimality of the addressed system.Finally,simulation results are provided to validate the effectiveness of the proposed approach.

关 键 词：Distributed optimization Multi-agent systems Model-free adaptive control Event-triggered mechanism 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]