Design and Optimization of Direct Torque Control for Brushless DC Motors using Non-Fragile PIDA Controller and BFOA

Miniature Reaction Wheel Brushless Direct Current (MRWBLDC) motors are widely employed in satellite attitude control systems because of their compact size and accurate torque control. Direct Torque Control (DTC) has fast response time and torque accuracy potential, but the time-averaged torque ripple around zero and the control voltages for each phase result in a complex control effort when used in space applications. To address these issues, this manuscript proposes an optimized DTC strategy employing a Non-Fragile Proportional Integral Derivative Acceleration (NF-PIDA) controller for enhanced satellite attitude performance. The major objective of this work is to minimize torque ripple and improve the dynamic response of the MRWBLDC Motor, thereby enhancing speed regulation and reducing torque fluctuations for superior motor performance. A Bitterling Fish Optimization Algorithm (BFOA) is employed to minimize both torque ripple and speed errors of the motor drive system. The proposed system consists of an MRWBLDC motor, NF-PIDA Controller, a Pulse Width Modulation (PWM) Inverter, a Hall Sensor Feedback System, and a Voltage Source Inverter (VSI) and is implemented in MATLAB. Comparative analysis with existing methods like Whale Optimization Algorithm (WOA), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) confirms the superior performance of BFOA in optimizing torque control and minimizing speed error. The proposed technique minimizes the torque ripple by 5 Nm and speed error by 10 rpm. The proposed control strategy significantly improves the dynamic performance and stability of MRWBLDC motors under varying operating conditions. Its effectiveness makes it wellsuited for high-precision applications such as satellite attitude control.