Human-in-the-Loop Consensus Control for Nonlinear Multi-Agent Systems With Actuator Faults

Guohuai Lin; Hongyi Li; Hui Ma; Deyin Yao; Renquan Lu

doi:10.1109/JAS.2020.1003596

Volume 9 Issue 1

Jan. 2022

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2022 > 9(1): 111-122

G. H. Lin, H. Y. Li, H. Ma, D. Y. Yao, and R. Q. Lu, “Human-in-the-loop consensus control for nonlinear multi-agent systems with actuator faults,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 1, pp. 111–122, Jan. 2022. doi: 10.1109/JAS.2020.1003596

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G. H. Lin, H. Y. Li, H. Ma, D. Y. Yao, and R. Q. Lu, “Human-in-the-loop consensus control for nonlinear multi-agent systems with actuator faults,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 1, pp. 111–122, Jan. 2022. doi: 10.1109/JAS.2020.1003596

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Human-in-the-Loop Consensus Control for Nonlinear Multi-Agent Systems With Actuator Faults

doi: 10.1109/JAS.2020.1003596

Guohuai Lin^1
,,
Hongyi Li^{1
,
,},
Hui Ma^1
,,
Deyin Yao^1
,,
Renquan Lu^1
,

School of Automation and Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control, Guangdong University of Technology, Guangzhou 510006, China

Funds: This work was partially supported by the National Natural Science Foundation of China (62033003, 62003098), the Local Innovative and Research Teams Project of Guangdong Special Support Program (2019BT02X353), and the China Postdoctoral Science Foundation (2019M662813, 2020T130124)

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Author Bio:
Guohuai Lin received the B.S. degree in electrical engineering and automation from Guangdong University of Petrochemical Technology, in 2018. He is currently pursuing the Ph.D. degree in control science and engineering at Guangdong University of Technology. His current research interests include adaptive control and human-in-the-loop control for multi-agent systems

Hongyi Li (Senior Member, IEEE) received the Ph.D. degree in intelligent control from University of Portsmouth, Portsmouth, UK, in 2012. He was a Research Associate with the Department of Mechanical Engineering, University of Hong Kong, and Hong Kong Polytechnic University, China. He was a Visiting Principal Fellow with the Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, Australia. He is currently a Professor with Guangdong University of Technology. His research interests include intelligent control, cooperative control, sliding mode control and their applications. He was a recipient of the 2016 and 2019 Andrew P. Sage Best Transactions Paper Awards from IEEE System, Man, Cybernetics Society, the Best Paper Award in Theory from ICCSS 2017 and the Zadeh Best Student Paper from IEEE ICCSS 2019, respectively. He has been in the editorial board of several international journals, including IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Transactions on Cognitive and Developmental Systems, SCIENCE CHINA Information Sciences, IEEE/CAA Journal of Automatica Sinica, Journal of Systems Science and Complexity, Neural Networks, Asian Journal of Control, Circuits, Systems and Signal Processing, and International Journal of Control, Automation and Systems. He has been Guest Editors of IEEE Transactions on Cybernetics and IET Control Theory and Applications. He is a member of the IFAC Technical Committee on Computational Intelligence in Control

Hui Ma received the B.S. degree in mathematics from Harbin Normal University, in 2016, the M.S. degree in applied mathematics from Bohai University, in 2019. She is pursuing the Ph.D. degree in control science and engineering in Guangdong University of Technology. Her current research interests include fuzzy control and adaptive control for nonlinear systems

Deyin Yao received the M.S. and Ph.D. degrees in Control Theory from Bohai University, and School of Automation, Guangdong University of Technology, China, in 2016 and 2019, respectively. He is currently a Postdoctoral at the School of Automation, Guangdong University of Technology. From 2018 to 2019, he was a joint Ph.D. student with the Department of Mechanical Engineering, University of Victoria, Victoria, Canada. His current research interests include multi-agent systems, sliding mode control and Markov jump systems

Renquan Lu (Senior Member, IEEE) received the Ph.D. degree in control science and engineering from Zhejiang University, in 2004. He is currently a Professor with the School of Automation, Guangdong University of Technology. His research was supported by the National Science Fund for Distinguished Young Scientists of China in 2014, honored as the Distinguished Professor of Pearl River Scholars Program of Guangdong Province in 2015, and the Yangtze River Scholars Program by the Ministry of Education of China in 2017. His current research interests include complex systems, networked control systems, and nonlinear systems
Corresponding author: Hongyi Li, e-mail: lihongyi2009@gmail.com
Received Date: 2020-09-21
Revised Date: 2020-10-28
Accepted Date: 2020-11-03

Available Online: 2020-11-28

Abstract

Abstract

This paper considers the human-in-the-loop leader-following consensus control problem of multi-agent systems (MASs) with unknown matched nonlinear functions and actuator faults. It is assumed that a human operator controls the MASs via sending the command signal to a non-autonomous leader which generates the desired trajectory. Moreover, the leader’s input is nonzero and not available to all followers. By using neural networks and fault estimators to approximate unknown nonlinear dynamics and identify the actuator faults, respectively, the neighborhood observer-based neural fault-tolerant controller with dynamic coupling gains is designed. It is proved that the state of each follower can synchronize with the leader’s state under a directed graph and all signals in the closed-loop system are guaranteed to be cooperatively uniformly ultimately bounded. Finally, simulation results are presented for verifying the effectiveness of the proposed control method.
- Actuator faults,
- distributed control,
- human-in-the-loop,
- neighborhood observer,
- nonlinear multi-agent systems (MASs)

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In this paper, the leader of the nonlinear MASs is considered as non-autonomous and the leader’s control input is time-varying, which is provided by the human operator. In addition, we remove the restriction assumption that a subset of followers can access the leader’s control input
Different from most existing results, the controller designed in this paper achieves the leader-following consensus via adaptive coupling strengths for online adjustment. Furthermore, the considered nonlinear MASs are more general than the high-order Brunovsky form nonlinear systems
By using the relative information of neighboring nodes, the neighborhood observer is designed to estimate the unmeasurable states of nonlinear MASs, and the neighborhood observer-based neural fault-tolerant controller with dynamic coupling gains is constructed to achieve the leader-following consensus of MASs

Human-in-the-Loop Consensus Control for Nonlinear Multi-Agent Systems With Actuator Faults

doi: 10.1109/JAS.2020.1003596

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