Adaptive Fault-Tolerant Consensus Tracking Control for Nonlinear Multi-Agent Systems With Double Semi-Markovian Switching Topologies and Unknown Control Directions

Chao Zhou; Zehui Mao; Bin Jiang; Xing-Gang Yan

doi:10.1109/JAS.2025.125285

IEEE/CAA Journal of Automatica Sinica

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C. Zhou, Z. Mao, B. Jiang, and X.-G. Yan, “Adaptive fault-tolerant consensus tracking control for nonlinear multi-agent systems with double semi-markovian switching topologies and unknown control directions,” IEEE/CAA J. Autom. Sinica, 2025. doi: 10.1109/JAS.2025.125285

Citation:

C. Zhou, Z. Mao, B. Jiang, and X.-G. Yan, “Adaptive fault-tolerant consensus tracking control for nonlinear multi-agent systems with double semi-markovian switching topologies and unknown control directions,” IEEE/CAA J. Autom. Sinica, 2025. doi: 10.1109/JAS.2025.125285

Citation:

C. Zhou, Z. Mao, B. Jiang, and X.-G. Yan, “Adaptive fault-tolerant consensus tracking control for nonlinear multi-agent systems with double semi-markovian switching topologies and unknown control directions,” IEEE/CAA J. Autom. Sinica, 2025. doi: 10.1109/JAS.2025.125285

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Adaptive Fault-Tolerant Consensus Tracking Control for Nonlinear Multi-Agent Systems With Double Semi-Markovian Switching Topologies and Unknown Control Directions

doi: 10.1109/JAS.2025.125285

Funds: This work was supported by the National Natural Science Foundation of China (62333011, 62020106003), the Natural Science Foundation of Jiangsu Province of China (BK20222012), the Fundamental Research Funds for the Central Universities (NE2024005), and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX24 0594)

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Author Bio:
Chao Zhou received the B.S. degree in mathematics and applied mathematics and the M.S. degree in mathematics from Qufu Normal University, Qufu, China, in 2018 and 2021, respectively. She is currently pursuing the Ph.D. degree in control science and engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China. Her current research interests include multi-agent systems, fault-tolerant control, and adaptive/robust control

Zehui Mao (Senior Member, IEEE) received the Ph.D. degree in control theory and control engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2009. She was a Visiting Scholar with the University of Virginia from October 2015 to November 2016. She is currently a Professor with the College of Automation Engineering, Nanjing University of Aeronautics and Astronautics. She worked in the areas of fault diagnosis and fault-tolerant control, with particular interests in nonlinear control systems, multi-agent systems, and spacecraft flight control applications. She currently serves as an Editorial Board Member for journals such as IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS and NEUROCOMPUTING, as well as a Young Editorial Board Member for IEEE/CAA JOURNAL OF AUTOMATICA SINICA

Bin Jiang (Fellow, IEEE) received the Ph.D. degree in automatic control from Northeastern University, Shenyang, China, in 1995. He has been a Post-Doctoral Fellow, a Research Fellow, an Invited Professor, and a Visiting Professor in Singapore, France, USA, and Canada, respectively. He is currently the President of Nanjing University of Aeronautics and Astronautics, Nanjing, China, and a Chair Professor with the Cheung Kong Scholar Program, Ministry of Education. He has authored eight books and over 100 referred international journal articles. His current research interests include intelligent fault diagnosis, fault-tolerant control, and their applications to helicopters, satellites, and high-speed trains. He is a fellow of Asia–Pacific Artificial Intelligence Association (AAIA) and the Chinese Association of Automation (CAA); the Chair of the Control Systems Chapter in the IEEE Nanjing Section; the President of Nanjing Branch of AAIA; and a member of the IFAC Technical Committee on Fault Detection, Supervision, and Safety of Technical Processes. He was a recipient of the National Natural Science Award of China. He currently serves as a Senior Editor for International Journal of Control, Automation and Systems and an Associate Editor or an Editorial Board Member for several journals, such as IEEE TRANSACTIONS ON CYBERNETICS, IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, and IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS

Xing-Gang Yan received the B.Sc. degree from Shaanxi Normal University in 1985, the M.Sc. degree from Qufu Normal University in 1991, and the Ph.D. degree in engineering from Northeastern University, China, in 1997. He worked as a Research Fellow/Research Associate at the Northwestern Polytechnical University, China; University of Hong Kong, Hong Kong; Nanyang Technological University, Singapore; and University of Leicester, U.K. He was a Lecturer at Qingdao University, China, from 1991 to 1994. Currently, he is a Senior Lecturer in Control Engineering with the University of Kent U.K. He has published three books, six invited book chapters, and over 200 refereed papers in the area of control engineering. His research interests include sliding mode control and decentralized control with applications in engineering systems. He serves as a TPC member for a number of international conferences. He received the Best Application Paper Award of the Asian Control Conference (ASCC), Fukuoka, Japan, in 2019. He is the Associate Editor of IET Control Theory & Applications, Complexity, and Energies
Corresponding author: Zehui Mao, e-mail: zehuimao@nuaa.edu.cn
¹ In this paper, the growth rate specifically refers to the exponent in the exponential function involved in the Nussbaum function, such as \begin{document}$ \chi_i^2 $\end{document} in \begin{document}$ e^{\chi_i^2} $\end{document} and \begin{document}$ \alpha|\chi_i| $\end{document} in \begin{document}$ e^{\alpha|\chi_i|} $\end{document}.
Received Date: 2024-07-30
Accepted Date: 2025-01-25

Available Online: 2025-03-14

Abstract

Abstract

This paper is concerned with adaptive consensus tracking control of nonlinear multi-agent systems with actuator faults and unknown nonidentical control directions under double semi-Markovian switching topologies. Considering the complex working environment and the stability differences in communication links between leaders and followers, a double semi-Markov process is first introduced to describe the random switching of communication topologies in the leader-follower structure. In order to address challenges from the unknown nonidentical control directions and partial loss of effectiveness actuator faults, a completely independent parameter is introduced into the Nussbaum function to overcome the inherent obstacle of mutual cancellation and avoid the rapid growth rate. Considering only the state information of agents is transmitted among the agents, an adaptive distributed fault-tolerant consensus tracking control is proposed based on the double semi-Markovian switching topologies using the designed Nussbaum function. Furthermore, the stability of the closed-loop nonlinear multi-agent systems is analyzed using contradiction argument and Lyapunov theorem, from which the asymptotic consensus tracking in mean square sense can be obtained. A numerical simulation example is provided to verify the effectiveness of the proposed algorithm.
- Adaptive control,
- consensus tracking,
- double semi-Markovian switching topologies,
- fault-tolerant control,
- nussbaum function,
- unknown nonidentical control directions

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¹ In this paper, the growth rate specifically refers to the exponent in the exponential function involved in the Nussbaum function, such as $ \chi_i^2 $ in $ e^{\chi_i^2} $ and $ \alpha|\chi_i| $ in $ e^{\alpha|\chi_i|} $.

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Adaptive Fault-Tolerant Consensus Tracking Control for Nonlinear Multi-Agent Systems With Double Semi-Markovian Switching Topologies and Unknown Control Directions

doi: 10.1109/JAS.2025.125285

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