Lion-Optimized ANFIS Control for a Hybrid PV–Wind–Battery System with a Reduced-Switch 31-Level Inverter for Induction Motor Drives

Abstract

This study proposes and experimentally validates a hybrid photovoltaic–wind–battery energy conversion system for driving a three-phase induction motor under variable renewable-source conditions. The system integrates a high-gain SEPIC converter, a PWM rectifier, a bidirectional battery converter, a reduced-switch 31-level cascaded H-bridge inverter, and a Lion Optimization Algorithm–tuned adaptive neuro-fuzzy inference system controller. The proposed controller performs maximum power point tracking and regulates the common DC-link voltage by adjusting the converter and rectifier switching commands in response to changes in solar irradiance, photovoltaic temperature, and wind-side voltage. The system was evaluated using MATLAB/Simulink and an FPGA-based experimental prototype. The photovoltaic array produced approximately 134 V and 75 A under the tested operating conditions, while the SEPIC converter and PWM rectifier maintained the DC-link voltage near 400 V. The battery state of charge remained around 60%, indicating balanced charging and discharging operation. The 31-level inverter generated a stable multilevel output with an RMS voltage of approximately 499 V and real power of approximately 4990 W. The simulated total harmonic distortion was 1.39%, while the experimental prototype achieved 2.85%. The experimental results were consistent with the simulation outcomes and confirmed the effectiveness of the proposed controller in improving transient response, reducing steady-state fluctuations, and maintaining stable power delivery to the induction motor. The proposed configuration provides a feasible solution for renewable-powered motor-drive and marine propulsion applications requiring high voltage gain, adaptive control, energy-storage coordination, and low harmonic distortion.