文章基本信息

标题：‘State Déjà vu’ inter-agent learning adaptive control framework
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作者：Hongyi Qu ; Ridong Zhang ; Furong Gao 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2016
卷号：49
期号：7
页码：984-989
DOI：10.1016/j.ifacol.2016.07.330
语种：English
出版社：Elsevier
摘要：An inter-agent learning adaptive control framework is proposed for mass production by using multi-agent system approach to enhance the convergence performance over the single agent control. The idea is to invoke agent-wise differences on estimated parameters of the online estimator in adaptive control. Each agent’s estimator selects estimated parameters from a corresponding ‘best’ agent among them for next iteration according to ‘State Déjà vu’ criterion mimicking psychological phenomenon of adopting experience from state similar to current one. The application of proposed framework on model free adaptive control shows to have robust convergence, good stability, and effective performances enhancement.
关键词：Nonlinear systemAdaptive controlParameter estimationLearning controlContinuous systemsRegulation