Title: A Gaussian-based adaptive control scheme for wireless power transfer systems using modified particle swarm optimisation

Authors: Xudong Gao; Lihong Chen; Wenjie Cao; Qiang Yang

Addresses: School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing 210044, China ' School of Computer Science, Nanjing University of Information Science and Technology, Nanjing 210044, China ' College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China ' School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing 210044, China

Abstract: In recent years, intelligent control schemes have gained prominence in wireless power transfer (WPT) systems, significantly influencing their time-domain performance. Most recent studies focus on global control strategies that employ a fixed set of controller parameters during operation. However, these strategies lack the capability to adaptively adjust parameters based on the system state, resulting in suboptimal responses. To address these limitations, this paper proposes a Gaussian-based adaptive control scheme for WPT systems. By integrating the Gaussian function into PWM-based SMC techniques, the controller can be dynamically adjusted in accordance with the system's behaviour, thereby enhancing system performance. Furthermore, the controller parameters are optimised using modified particle swarm optimisation for dynamical changes of the control system design, leading to further improvement of system performance. Furthermore, simulations are presented to prove the effectiveness of the proposed adaptive control scheme.

Keywords: Gaussian adaptive technique; adaptive sliding mode control; modified particle swarm optimisation; wireless power transfer system.

DOI: 10.1504/IJAMECHS.2026.153253

International Journal of Advanced Mechatronic Systems, 2026 Vol.13 No.2, pp.91 - 103

Received: 30 Dec 2024
Accepted: 25 Apr 2025
Published online: 29 Apr 2026 *

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