ELM-Based Adaptive Practical Fixed-Time Voltage Regulation in Wireless Power Transfer System

Youhao Hu, Bowang Zhang, Weikang Hu and Wei Han ()
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Youhao Hu: Sustainable Energy and Environment Thrust, Function Hub, The Hong Kong University of Science and Technology (Guangzhou), Nansha, Guangzhou 511400, China
Bowang Zhang: Sustainable Energy and Environment Thrust, Function Hub, The Hong Kong University of Science and Technology (Guangzhou), Nansha, Guangzhou 511400, China
Weikang Hu: Sustainable Energy and Environment Thrust, Function Hub, The Hong Kong University of Science and Technology (Guangzhou), Nansha, Guangzhou 511400, China
Wei Han: Sustainable Energy and Environment Thrust, Function Hub, The Hong Kong University of Science and Technology (Guangzhou), Nansha, Guangzhou 511400, China

Energies, 2023, vol. 16, issue 3, 1-19

Abstract: This paper proposes an extreme learning machine (ELM)-based adaptive sliding mode control strategy for the receiver-side buck converter system in the wireless power transfer system subjecting to the lumped uncertainty. The proposed control strategy utilizes a singularity-free fixed-time sliding mode (FTSM) feedback control, which ensures a fixed-time convergence for both the sliding variable and voltage tracking error. An ELM-based uncertainty bound estimator is further designed to learn the uncertainty bound information in real-time, which opportunely loosens the constraint of bound information requirement for sliding mode control design. The global stability of the closed-loop system is rigidly analyzed, and the good performance of the proposed control strategy is validated by comparison experiments which exhibit ideal overshoot elimination, 45.70–51.72% reduction of settling time, and 13.65–36.96% reduction of the root mean square value for voltage tracking error with respect to different load types.

Keywords: fixed time sliding mode; extreme learning machine; wireless power transfer; buck converter (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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