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Research Article | Open Access

Prescribed-time trajectory tracking control for a class of nonlinear system

Lichao Feng1( )Chunlei Zhang1Mahmoud Abdel-Aty2,3Jinde Cao4( )Fawaz E. Alsaadi5
College of Electrical Engineering and College of Science, North China University of Science and Technology, Tangshan 063210, China
Deanship of Graduate Studies and Scientific Research, Ahlia University, Manama 10878, Bahrain
Jadara Research Center, Jadara University. P.O.Box 733, Irbid 21110, Jordan
School of Mathematics, Southeast University, Nanjing 210096, China
Communication Systems and Networks Research Group, Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
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Abstract

Previous works have analyzed finite/fixed-time tracking control for nonlinear systems. In these works, achieving the accurate time convergence of errors must be under the premise of known initial values and careful design of control parameters. Then, how to break through the constraints of initial values and design parameters for this issue is an unsolved problem. Motivated by this, we successfully studied prescribed-time tracking control for single-input single-output nonlinear systems with uncertainties. Specifically, we designed a state feedback controller on [0,Tp), based on the backstepping method, to make the tracking error (TE) tend to zero at Tp, in which Tp is the arbitrarily selected prescribed-time. Furthermore, on [Tp,), another controller, similarly to that on [0,Tp), was designed to keep TE within a precision after Tp, while TE may not stay at zero. Therefore, on [Tp,), another new controller, based on sliding mode control, was built to ensure that TE stays at zero after Tp.

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Electronic Research Archive
Pages 6535-6552

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Cite this article:
Feng L, Zhang C, Abdel-Aty M, et al. Prescribed-time trajectory tracking control for a class of nonlinear system. Electronic Research Archive, 2024, 32(12): 6535-6552. https://doi.org/10.3934/era.2024305

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Received: 11 October 2024
Revised: 14 November 2024
Accepted: 20 November 2024
Published: 15 December 2024
©2024 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)