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Iterative Learning Consensus Control for Multi-agent Systems with Fractional Order Distributed Parameter Models

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Abstract

This paper concerns about the iterative learning consensus control scheme for a class of multi-agent systems (MAS) with distributed parameter models. First, based on the framework of network topologies, a second-order iterative learning control (ILC) protocol is proposed by using the nearest neighbor knowledge. Next, a discrete system for ILC is established and the consensus control problem is then converted to a stability problem for such a discrete system. Furthermore, by using generalized Gronwall inequality, a sufficient condition for the convergence of the consensus errors between any two agents is obtained. Finally, the validity of the proposed method is verified by two numerical examples.

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Authors and Affiliations

  1. School of Information Engineering, Xiangtan University, Xiangtan, Hunan, 411105, P. R. China

    Yong-Hong Lan, Jun-Jun Xia, Ya-Ping Xia & Peng Li

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  1. Yong-Hong Lan
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Correspondence to Peng Li.

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Recommended by Editor Fumitoshi Matsuno. This work is supported by the National Natural Science Foundation of PR China (61573298), Key R and D Project in Hunan Province (2018GK2014) and The MOE Key Laboratory of Intelligent Computing and Information Processing.

Yong-Hong Lan received his B.S. and M.S. degrees in Applied Mathematics from Xiangtan University, Xiangtan, China, in 1999 and 2004, respectively; and his Ph.D. degree in Control Theory and Control Engineering from Central South University, Changsha, China in 2010. He is currently a professor in the School of Information Engineering, Xiangtan University, Xiangtan, China. His current research interests are fractional order control systems and iterative learning control.

Jun-Jun Xia received her B.S. degree in Measurement, Control Technology and Instruments from Zhongyuan University of Technology, Zhengzhou, China in 2015. She is a Master degree candidate student in Control Engineering from Xiangtan University, Xiangtan, China. Her current research interests are iterative learning control and multi-agent system.

Ya-Ping Xia received her Ph.D. degree in control theory and control engineering from Nanjing University of Science and Technology, Nanjing, China in 2016. She is a lecturer in the College of Information and Engineering, Xiangtan University. Her research interests include control theory and application, wind power conversion system.

Peng Li received his B.S. degrees in Automation and M.S. degree in Control Theory and Control Engineering from Harbin University of Science and Technology, Harbin, China, in 2003 and 2006, respectively; and his Ph.D. degree in Control Science and Engineering from Harbin Institute of Technology, Harbin, China in 2010. He is currently an associate professor in the School of Information Engineering, Xiangtan University, Xiangtan, China. His current research interests are fractional order control systems, iterative learning control and Multi-Agent Navigation.

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Lan, YH., Xia, JJ., Xia, YP. et al. Iterative Learning Consensus Control for Multi-agent Systems with Fractional Order Distributed Parameter Models. Int. J. Control Autom. Syst. 17, 2839–2849 (2019). https://doi.org/10.1007/s12555-018-0595-7

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