Metaheuristic Adaptive Input Output Feedback Linearization Control for BLDC Motor Drive

Electric unmanned aerial vehicles (UAVs) demanding complex maneuvering for various applications require precise control of the brushless direct current (BLDC) motor, an essential part of the electric propulsion system. The present work suggests adaptive input-output feedback linearization (IOFL) based field-oriented control (FOC) for precise and quick tracking of the reference speed demanded by flight controllers with tolerable torque ripples. The IOFL control generates the reference voltages for a three-phase inverter circuit. The suggested approach performs reliably even when the temperature changes, owing to the adaptive mechanism that calculates the stator resistance. An enhanced metaheuristic algorithm based on stochastic fractal search (SFS) helps optimize the tuning parameters for PI regulators. In addition, the SFS algorithm, compared with particle swarm optimization (PSO), shows superior performance and faster convergence of the SFS algorithm. The Lyapunov stability analysis helps verify the stability of the proposed controller to ensure reliable functioning under all operating circumstances. Finally, the proposed scheme’s operational performance is evaluated through TMS320F28379D microcontroller and BOOSTXL-DRV8305EVM three-phase inverter module under UAVs’ take-off, hovering, and landing states and compared with classical FOC to demonstrate convergence, robustness, and effectiveness.