Universal Intermittent State-Constrained Control Without Feasibility Condition for Nonlinear Systems

Xiaohui Yue; Huaguang Zhang; Jiayue Sun; Xiyue Guo

doi:10.1109/JAS.2025.125357

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2025 > In Press, Accepted Manuscript

X. Yue, H. Zhang, J. Sun, and X. Guo, “Universal intermittent state-constrained control without feasibility condition for nonlinear systems,” IEEE/CAA J. Autom. Sinica, 2025. doi: 10.1109/JAS.2025.125357

Citation:

X. Yue, H. Zhang, J. Sun, and X. Guo, “Universal intermittent state-constrained control without feasibility condition for nonlinear systems,” IEEE/CAA J. Autom. Sinica, 2025. doi: 10.1109/JAS.2025.125357

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Universal Intermittent State-Constrained Control Without Feasibility Condition for Nonlinear Systems

doi: 10.1109/JAS.2025.125357

Funds: This work was supported by the Fundamental Research Funds for the Central Universities (N2404005), the National Key Research and Develepment Program of China (2018YFA0702200), Liaoning Revitalization Talents Program (XLYC1801005), the National Natural Science Foundation of China (U23B20118), and the Nature Science Foundation of Liaoning Province of China (2022JH25/10100008)

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Author Bio:
Xiaohui Yue (Student Member, IEEE) received the B.S. degree in measurement and control technology and instruments and the M.S. degree in instrument science and technology from North University of China in 2019 and 2022, respectively. He is currently pursuing the Ph.D. degree in control science and engineering with Northeastern University.His research interests include nonlinear system control, intelligent adaptive control, target enclosing control, vehicle control, and cooperative control of multi-agent systems

Huaguang Zhang (Fellow, IEEE) received the B.S. and M.S. degrees in control engineering from the Northeast Dianli University of China in 1982 and 1985, respectively, and the Ph.D. degree in thermal power engineering and automation from Southeast University in 1991. He joined the Department of Automatic Control, Northeastern University in 1992, as a Post-Doctoral Fellow, for two years, where he has been a Professor and the Head of the Institute of Electric Automation, College of Information Science and Engineering, since 1994. He has authored or co-authored over 200 journal and conference papers and four monographs and has co-invented 20 patents.His research interests include fuzzy control, stochastic-system control, neural- network-based control, nonlinear control, and their applications. He was a recipient of the Outstanding Youth Science Foundation Award from the National Natural Science Foundation Committee of China in 2003. He was named the Cheung Kong Scholar by the Education Ministry of China in 2005. He is an Associate Editor of Automatica, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Cybernetics

Jiayue Sun (Member, IEEE) received the Ph.D. degree in power electronics and power transmission from Northeastern University, under the supervision of IEEE Fellow Huaguang Zhang, in 2021.She is a postdoctoral fellow under Tianyou Chai (a member of the Chinese Academy of Engineering, IEEE Life Fellow), at the State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University. Now She is a Teacher at Northeastern University, a member of the Chinese Association of Automation (CAA) and Chinese Association for Artificial Intelligence (CAAI), and works as the Intelligent Adaptive Learning Committee’s secretary of CAAI. She has authored or co-authored 30 peer-reviewed international journal papers.Her research interests include optimization of complex industrial processes, intelligent adaptive learning, and distributed control of multi-agent systems

Xiyue Guo received the B.S. degree in automation from Shandong Technology and Business University in 2018. He received the M.S. degree in Pattern Recognition and Intelligent Systems from Bohai University in 2021. He is currently pursuing the Ph.D. degree in control science and engineering with Northeastern University.His research interests include adaptive fuzzy control and cooperative control for stochastic multi-agent systems
Corresponding author: Huaguang Zhang, e-mail: hgzhang@ieee.org
Received Date: 2024-12-27
Accepted Date: 2025-02-21

Available Online: 2025-06-19

Abstract

Abstract

State constraints in nonlinear systems are commonly pursued by resorting to barrier functions, which enforce constraints over the entire duration of system operation. We propose a universal intermittent state-constrained solution, which not only offers flexibility by activating constraints just during specific time periods of interest to the user, but also successfully accommodates different types of constraint boundaries. The innovative shifting functions are proposed to facilitate seamless transitions between constrained and unconstrained operational phases, resulting in more user-friendly design and implementation. By blending an improved shifting transformation into intermittent constraint design, we construct a universal barrier function upon the constrained states, with which our control strategy removes the limitations on constraint functions and completely obviates the feasibility conditions. Furthermore, a modified fuzzy approximator driven by the prediction error rather than the tracking error achieves decoupling of the control and estimation loops, which not only ensures the estimation performance, but also facilitates proof of stability. Finally, the effectiveness of the proposed scheme is assessed by numerical simulation.
- Fuzzy approximator,
- intermittent state constraints (ISCs),
- nonlinear systems,
- universal barrier functions (UBF)

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Universal Intermittent State-Constrained Control Without Feasibility Condition for Nonlinear Systems

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