Adaptive Prescribed-Time Exact Tracking Control for Uncertain Strict-Feedback Systems With Global Prescribed-Performance

Yizhaotun Yan; Bing Mao; Ling Lei; Hui Liu; Xiaoqun Wu

doi:10.1109/JAS.2025.125966

Volume 13 Issue 5

May 2026

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2026 > 13(5): 1166-1175

Y. Yan, B. Mao, L. Lei, H. Liu, and X. Wu, “Adaptive prescribed-time exact tracking control for uncertain strict-feedback systems with global prescribed-performance,” IEEE/CAA J. Autom. Sinica, vol. 13, no. 5, pp. 1166–1175, May 2026. doi: 10.1109/JAS.2025.125966

Citation:

Y. Yan, B. Mao, L. Lei, H. Liu, and X. Wu, “Adaptive prescribed-time exact tracking control for uncertain strict-feedback systems with global prescribed-performance,” IEEE/CAA J. Autom. Sinica, vol. 13, no. 5, pp. 1166–1175, May 2026. doi: 10.1109/JAS.2025.125966

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Adaptive Prescribed-Time Exact Tracking Control for Uncertain Strict-Feedback Systems With Global Prescribed-Performance

doi: 10.1109/JAS.2025.125966

Funds: This work was supported by the National Natural Science Foundation of China (62503335, 92267101, 62573301)

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Author Bio:
Yizhaotun Yan received the B.Sc. degree in applied mathematics from Wuhan University in 2022. He is currently a master student in applied mathematics at Wuhan University. His current research interests include prescribed performance control and prescribed-time control

Bing Mao (Member, IEEE) received the B.Sc. and the Ph.D. degrees in applied mathematics from Wuhan University, in 2019 and 2024, respectively. He is now an Assistant Professor with the College of Computer Science and Software Engineering at Shenzhen University. His current research interests include prescribed performance control and cooperative control of multiagent systems

Ling Lei received the B.Sc. degree in mathematics and the M.Sc. degree in operations research and control theory from Central China Normal University in 2001 and 2004, respectively, and the Ph.D. degree in operations research and control theory from Zhejiang University in 2007. She is currently working as an Associate Professor with the School of Mathematics and Statistics, Wuhan University. Her research interests include optimal control theory and computer vision

Hui Liu (Member, IEEE) received the B.Sc. and Ph.D. degrees in computational mathematics from Wuhan University, in 2005 and 2010, respectively, the Ph.D. degree in the field of systems and control from the University of Groningen, the Netherlands, in 2013. She is currently an Associate Professor with the School of Artificial Intelligence and Automation, Huazhong University of Science and Technology. Her main research interests include complex networks, cooperative control of networked systems, and intelligent control systems. She held visiting positions with the Academy of Mathematics and Systems Science, Chinese Academy of Sciences, and with the Department of Electronic and Information Engineering, the Hong Kong Polytechnic University, Hong Kong, China

Xiaoqun Wu (Member, IEEE) received the B.Sc. degree in applied mathematics and the Ph.D. degree in computational mathematics from Wuhan University, in 2000 and 2005, respectively. Currently, she serves as a Distinguished Professor at the College of Computer Science and Software Engineering, Shenzhen University. Prior to this, she was a Professor at the School of Mathematics and Statistics, Wuhan University, and held several visiting positions in Hong Kong, China, Australia and USA. Her current research interests include parameter identification and control of networked systems. She has published over 130 SCI journal papers in these areas. She was a recipient of the Second Prize of the Natural Science Award from the Hubei Province, China in 2006, the First Prize of the Natural Science Award from the Ministry of Education of China in 2007, and the First Prize of the Natural Science Award from the Hubei Province, China in 2013. In 2017, she was awarded the 14th Chinese Young Women Scientists Fellowship and the Natural Science Fund for Distinguished Young Scholars of Hubei Province. She has been serving as an Associate Editor for IEEE Transactions on Circuits and Systems II since 2018
Corresponding author: Bing Mao, e-mail: bingmao@szu.edu.cn; Xiaoqun Wu, e-mail: xqwu@whu.edu.cn
Received Date: 2025-04-29
Accepted Date: 2025-10-03

Abstract

Abstract

For uncertain strict-feedback systems under the prescribed performance control (PPC) problem, an innovative adaptive prescribed-time tracking control method is proposed. This method combines a novel error transformation function with the prescribed-time stability theory, thereby achieving exact tracking of desired trajectories within a prescribed time while ensuring that the tracking error stays within predefined boundaries globally. By integrating a newly-designed Lyapunov-like energy function with dynamic surface control, it resolves the error surface issues that result in the semi-global boundedness of tracking error in traditional approaches. Furthermore, through a generalized Filippov solution definition, this approach overcomes the issue of non-existence of the system solution, which arises during the prescribed-time stability analysis due to the discontinuous control input. Simulation results validate the effectiveness of the proposed method.
- Dynamic surface control,
- global prescribed performance,
- mismatched uncertainty,
- prescribed-time exact tracking,
- strict-feedback nonlinear systems

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References(40)

References

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