文章基本信息

标题：A Passivity-Based Distributed Reference Governor for Constrained Robotic Networks
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作者：Tam Nguyen ; Takeshi Hatanaka ; Mamoru Doi 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2017
卷号：50
期号：1
页码：15434-15439
DOI：10.1016/j.ifacol.2017.08.1875
语种：English
出版社：Elsevier
摘要：AbstractThis paper focuses on a passivity-based distributed reference governor (RG) applied to a pre-stabilized mobile robotic network. The novelty of this paper lies in the method used to solve the RG problem, where a passivity-based distributed optimization scheme is proposed. In particular, the gradient descent method minimizes the global objective function while the dual ascent method maximizes the Hamiltonian. To make the agents converge to the agreed optimal solution, a proportional-integral consensus estimator is used. This paper proves the convergence of the state estimates of the RG to the optimal solution through passivity arguments, considering the physical system static. Then, the effectiveness of the scheme considering the dynamics of the physical system is demonstrated through simulations and experiments.
关键词：KeywordsDistributed controlestimationControl of networksMobile robotsConvex optimizationControl under communication constraints