Decentralized Prescribed-Time Output-Feedback Control for Interconnected Systems With Coupled Non-Identical Subsystems of Different Orders

Yan Tan; Hefu Ye; Changyun Wen; Yongduan Song

doi:10.1109/JAS.2025.125918

Volume 13 Issue 5

May 2026

IEEE/CAA Journal of Automatica Sinica

JCR Impact Factor: 19.2, Top 1 (SCI Q1)

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2026 > 13(5): 1097-1107

Y. Tan, H. Ye, C. Wen, and Y. Song, “Decentralized prescribed-time output-feedback control for interconnected systems with coupled non-identical subsystems of different orders,” IEEE/CAA J. Autom. Sinica, vol. 13, no. 5, pp. 1097–1107, May 2026. doi: 10.1109/JAS.2025.125918

Citation:

Y. Tan, H. Ye, C. Wen, and Y. Song, “Decentralized prescribed-time output-feedback control for interconnected systems with coupled non-identical subsystems of different orders,” IEEE/CAA J. Autom. Sinica, vol. 13, no. 5, pp. 1097–1107, May 2026. doi: 10.1109/JAS.2025.125918

Citation:

Y. Tan, H. Ye, C. Wen, and Y. Song, “Decentralized prescribed-time output-feedback control for interconnected systems with coupled non-identical subsystems of different orders,” IEEE/CAA J. Autom. Sinica, vol. 13, no. 5, pp. 1097–1107, May 2026. doi: 10.1109/JAS.2025.125918

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Decentralized Prescribed-Time Output-Feedback Control for Interconnected Systems With Coupled Non-Identical Subsystems of Different Orders

doi: 10.1109/JAS.2025.125918

Funds: This work was supported by the National Key Research and Development Program of China (2022YFB4701400/4701401) and the National Natural Science Foundation of China (61991400, 61991403, 62250710167, 61860206008, 61933012, 62273286, 62403082)

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Author Bio:
Yan Tan received the B.S. in information and computing science degree from the School of Mathematical Sciences, Chongqing Normal University in 2019, and the M.S. degree in systems science from the School of Science, Kunming University of Science and Technology in 2024. She is currently a Ph.D. degree candidate in control science and engineering at Chongqing University. Her research interests include adaptive and learning systems, prescribed-time control, decentralized control, and networked systems

Hefu Ye (Member, IEEE) received the B.E. degree in measurement and control technology and instrument from Harbin Institute of Technology in 2019, and the Ph.D. degree in control science and engineering from Chongqing University in 2025. From 2022 to 2023, he was a joint Ph.D. degree candidate at the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. Following the completion of his Ph.D. degree, he served as a Research Associate in the Department of Mechanical Engineering at The University of Hong Kong, China. Since September 2025, he has been a Postdoctoral Fellow with the Faculty of Science and Technology at the University of Macau, Macau, China. His research interests include robotic control, decentralized control, and prescribed-time control.Dr. Ye was a recipient of the 2025 Andrew P. Sage Best Transactions Paper Award from IEEE Systems, Man, Cybernetics Society. He is also an Active Reviewer for several international journals, including the Automatica, IEEE Transactions on Automatic Control, SIAM Journal on Control and Optimization, and IEEE/ASME Transactions on Mechatronics

Changyun Wen (Fellow, IEEE) received the B.E. degree from Xi’an Jiaotong University in 1983, and the Ph.D. degree from the University of Newcastle, Australia in 1990. From August 1989 to August 1991, he was a Postdoctoral Fellow at University of Adelaide, Australia. Since August 1991, he has been with Nanyang Technological University, Singapore, where he is currently a Full Professor. His main research activities are in the areas of control systems and applications, cyber-physical systems, smart grids, complex systems and networks.Prof. Wen is a Fellow of the Academy of Engineering, Singapore. He was a Member of IEEE Fellow Committee from January 2011 to December 2013 and a Distinguished Lecturer of IEEE Control Systems Society from 2010 to 2013. He is currently the Co-Editor-in-Chief of IEEE Transactions on Industrial Electronics, Associate Editor of Automatica (from Feb. 2006) and Executive Editor-in-Chief of Journal of Control and Decision. He also served as an Associate Editor of IEEE Transactions on Automatic Control from 2000 to 2002, IEEE Transactions on Industrial Electronics from 2013 to 2020 and IEEE Control Systems Magazine from 2009 to 2019. He has been actively involved in organizing international conferences playing the roles of General Chair (including the General Chair of IECON 2020 and IECON 2023), TPC Chair (e.g., the TPC Chair of Chinese Control and Decision Conference since 2008), etc. He was the recipient of a number of awards, including the Prestigious Engineering Achievement Award from the Institution of Engineers, Singapore in 2005, and the Best Paper Award of IEEE Transactions on Industrial Electronics in 2017

Yongduan Song (Fellow, IEEE) received the Ph.D. degree in electrical and computer engineering from Tennessee Technological University, USA, in 1992. He held a tenured Full Professor with North Carolina A&T State University, USA, from 1993 to 2008 and a Langley Distinguished Professor with the National Institute of Aerospace, USA, from 2005 to 2008. He is currently the Dean of the Institute of Artificial Intelligence, Chongqing University. He was one of the six Langley Distinguished Professors with the National Institute of Aerospace (NIA), USA, and the Founding Director of Cooperative Systems with NIA. His current research interests include intelligent systems, guidance navigation and control, bio-inspired adaptive and cooperative systems.Prof. Song was a recipient of several competitive research awards from the National Science Foundation, the National Aeronautics and Space Administration, the U.S. Air Force Office, the U.S. Army Research Office, and the U.S. Naval Research Office. He has served/been serving as an Associate Editor for several prestigious international journals, including the IEEE Transactions on Automatic Control, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Transactions on Intelligent Transportation Systems, etc. He is currently Editor-in-Chief for the IEEE Transactions on Neural Networks and Learning Systems. He is a Foreign Member of the Chinese Academy of Engineering
Corresponding author: Yongduan Song, e-mail: ydsong@cqu.edu.cn
Received Date: 2025-05-11
Revised Date: 2025-08-06
Accepted Date: 2025-09-09

Abstract

Abstract

The challenge of decentralized control arises from the necessity to use only local information for constructing feedback mechanisms, with the goal of suppressing interactions among subsystems while ensuring the overall stability and performance of the entire system. The problem is significantly complicated when interconnected subsystems possess non-identical nonlinear dynamics with arbitrary relative degrees. We propose a novel time-varying decentralized control architecture that achieves global prescribed-time stabilization for the overall system through local output feedback. The developed scheme guarantees convergence to the equilibrium within any user-defined time interval, with temporal performance decoupled from initial conditions and independent of other controller parameter selection. Firstly, the decentralized prescribed-time observers for subsystems are systematically constructed to reconstruct full-state information, forming the basis for output-feedback synthesis. Secondly, a decentralized matrix pencil framework is established by incorporating symmetric positive-definite solutions of parametric Lyapunov equations, enabling concurrent management of intra-subsystem state/observer error dynamics and inter-subsystem couplings. This strategy facilitates the derivation of low-conservative design parameters while enhancing the applicability of the control algorithm. Finally, our findings demonstrate that the proposed approach is capable of accommodating a general system model characterized by unknown interaction strengths and arbitrary relative degrees. The theoretical results are validated through two simulation examples, confirming the effectiveness of the developed control scheme.
- Decentralized control,
- interconnected systems,
- output-feedback,
- prescribed-time control

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References(48)

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