Genetic Algorithm-Based Cerebellar Model Controller Simulation for Permanent Magnet Brushless DC Motor Mathematical Model

This document presents a simulation methodology employing a genetic algorithm-optimized cerebellar model controller for analyzing the mathematical model of permanent magnet brushless DC motors. We provide complete program code (including MATLAB scripts for genetic algorithm implementation and cerebellar model articulation controller - CMAC tuning) along with ready-to-run Simulink simulation models. The implementation demonstrates key functions such as population initialization, fitness evaluation based on motor performance metrics, crossover/mutation operations for controller optimization, and CMAC weight updating mechanisms. This simulation approach enables comprehensive investigation of motor characteristics including torque-speed relationships, current waveforms, and dynamic responses under varying load conditions. The provided materials serve as a practical foundation for designing and optimizing motor control systems, with particular emphasis on parameter tuning techniques for improved controller performance. These resources aim to facilitate deeper understanding and inspire further research in advanced motor control strategies.