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Group-consensus with Reference States for Heterogeneous Multiagent Systems via Pinning Control

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  • Control Theory and Applications
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Abstract

This paper considers group-consensus with reference states for heterogeneous multiagent systems, which is composed of first-order agents and second-order agents. The pinning scheme is induced for solving group-consensus under fixed and switching topologies, respectively. Firstly, a group-consensus control protocol via pining scheme under fixed topology is proposed. Then the corresponding sufficient conditions to guarantee group-consensus are deduced by employing graph theory and Lyapunov stability approach. What’s more, based on pinning scheme, the agents in every group can reach their own group’s reference states. Secondly, the group-consensus for heterogeneous multiagent systems with switching topologies is studied, where an equivalent system of the original multiagent system is obtained by model transformation. Then, the corresponding sufficient conditions to guarantee group-consensus are obtained based on the corresponding graph theory and Lyapunov stability approach. The same as the case of fixed topology, the agents in every group can also reach their own group’s reference states by employing pinning control. Finally, some simulation examples are presented to illustrate the capabilities of the established theories.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Beijing Jiaotong University, Beijing, 100044, PR China

    Jun Huang & Guoguang Wen

  2. School of Transportation Science and Engineering, Beihang University, Beijing, 100191, PR China

    Zhaoxia Peng

  3. National Pilot School of Software, Yunnan University, Kunming, China

    Xing Chu

  4. Beijing C&W electronics (Group) Co., Ltd, Beijing, 100015, China

    Youwei Dong

Authors
  1. Jun Huang
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  2. Guoguang Wen
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  3. Zhaoxia Peng
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  4. Xing Chu
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  5. Youwei Dong
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Corresponding author

Correspondence to Guoguang Wen.

Additional information

Recommended by Associate Editor Jiuxiang Dong under the direction of Editor Fuchun Sun. This work was supported by the Fundamental Research Funds for the Central Universities under Grants 2017YJS197, 2017JBM067, 2015JBM106, 2015RC039, YWF-14-RSC-032 and YWF-15-SYSJTXY- 007, the National Natural Science Foundation of China under Grants 61503016 and 61403019, and the National Key Research and Development Program of China under Grant 2017YFB0103202.

Jun Huang received the B.S. degree in Beijing Jiaotong University in 2016. Currently, she studies for a Ph.D. scholar position from Department of Mathematics, School of Science, Beijing Jiaotong University, China. Her research interest focuses on cooperative control for multiagent systems.

Guoguang Wen received his B.S degree in Department of Mathematical Science, Inner Mongolia University, China in 2007, an M.S. degree in Department of Mathematics, School of Science, Beijing Jiaotong University, China in 2009, and a Ph.D. degree in LAGIS, UMR 8219 CNRS, Ecole Centrale de Lille, France, in 2012. He is currently an Associate Professor with the Department of Mathematics School of Science, Beijing Jiaotong University, China. His research interest focuses on cooperative control for multi-agent systems, control of multi-robots formation, control of fractional systems, nonlinear dynamics and control, neural networks.

Zhaoxia Peng received her B.S degree in Department of Mathematical Science, Inner Mongolia University, China in 2007, an M.S. degree in Department of Mathematics, School of Science, Beijing Jiaotong University, China in 2009, and a Ph.D. degree in LAGIS, UMR 8219 CNRS, Ecole Centrale de Lille, France, in 2012. Currently, she is an Associate Professor with School of Transportation Science and Engineering, Beihang University, Beijing, China. Her research interest focuses on formation control for multiple mobile robots, multiagent systems, and neural networks.

Xing Chu received his B.S. degree at the Department of Automotive Engineering, Kunming University of Science and Technology, China, in 2011, and his M.S. degree at the Department of Mechanical Engineering, Hunan University, China, in 2014. He received his Ph.D. degree at CRIStAL, UMR CNRS 9189, Ecole Centrale de Lille, France, in 2017. Currently, he is is working at National Pilot School of Software, Yunnan University, Kunming, China. His research interests involve distributed control, estimate and computation; formation control; event-triggered control, finite-time control, deep learning and data mining.

Youwei Dong received his B.S degree in Ecole Centrale de Pekin, Beihang University, China in 2010, an M.S. degree in Ecole Centrale de Pekin, Beihang University, China in 2012, and a Ph.D. degree in LAGIS, UMR 8219 CNRS, Ecole Centrale de Lille, France, in 2016. He is currently a robotics specialist in Beijing C & W Electronics (Group) Co., Ltd., China. His research interest focuses on laser-based SLAM, localization and path planning of the service robot, cooperation strategy in Multi-Robot System.

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Huang, J., Wen, G., Peng, Z. et al. Group-consensus with Reference States for Heterogeneous Multiagent Systems via Pinning Control. Int. J. Control Autom. Syst. 17, 1096–1106 (2019). https://doi.org/10.1007/s12555-017-0706-x

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  • DOI: https://doi.org/10.1007/s12555-017-0706-x

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