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

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