A Novel Predefined Time PD-Type ILC Paradigm for Nonlinear Systems

Chun-Wu Yin, Saleem Riaz, Haider Zaman, Nasim Ullah (), Vojtech Blazek (), Lukas Prokop and Stanislav Misak
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Chun-Wu Yin: School of Information and Control Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China
Saleem Riaz: School of Automation, Northwestern Polytechnical University, Xi’an 710129, China
Haider Zaman: Electronics Engineering Department, University of Engineering and Technology Peshawar, Peshawar 25000, Pakistan
Nasim Ullah: Department of Electrical Engineering, College of Engineering, Taif University, Taif 11099, Saudi Arabia
Vojtech Blazek: ENET Centre, VSB—Technical University of Ostrava, 708 00 Ostrava, Czech Republic
Lukas Prokop: ENET Centre, VSB—Technical University of Ostrava, 708 00 Ostrava, Czech Republic
Stanislav Misak: ENET Centre, VSB—Technical University of Ostrava, 708 00 Ostrava, Czech Republic

Mathematics, 2022, vol. 11, issue 1, 1-19

Abstract: Intelligent robotics has drawn a great deal of attention due to its high precision, stability, and reliability, which are the basic key factors for industrial automation. This paper proposes an iterative learning control (ILC) technique with predefined-time convergence as a solution to an applied engineering problem, namely, that local time cannot be preset when a second-order nonlinear system undertakes control of the accurate tracking of local time under any initial iterative value. A time-varying sliding surface with an initial value of zero was designed, and it was theoretically proven that the trajectory tracking error in the sliding surface could converge to zero within a predefined time. The iterative control problem of trajectory tracking was thus changed to an iterative control problem of time-varying sliding-mode surface tracing with a starting value of zero. A PD-type closed-loop ILC with a time-varying sliding mode surface was designed such that the trajectory tracking error converged and stabilized on the sliding mode surface after a finite number of learning iterations. The control goal for the system’s output was the ability to track the desired trajectory accurately within a predefined time interval, and it was achieved by combining this with the predefined time convergence characteristics of the time-varying sliding mode surface. Numerical simulation of trajectory tracking control of a repetitive motion manipulator was used to verify the effectiveness of the proposed controller and its robustness in the face of external disturbances.

Keywords: iterative learning control; sliding mode control; predefined-time convergence; time-varying sliding mode surface; robotic arm (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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