PID Controller for PMSM Speed Control Based on Improved Quantum Genetic Algorithm Optimization
چکیده
When traditional proportional integral and differential controllers are applied to speed control in permanent magnet synchronous motors(PMSM), their coefficients basically determined based on experience, which inevitably leads unsatisfactory results when using this parameter the stability of motors. Therefore, paper proposes an improved quantum genetic algorithm states as basic unit. Utilizing properties for global optimization optimize control, improving rotation angle state particles through idea velocity changes particle swarm optimization(PSO), introducing adaptive weight changes, Hadamard gates replace mutation strategies, incorporating disaster mechanisms. In addition, uses four test functions find minimum value, thereby verifying that our has better performance iteration compared other algorithms, providing initial basis next step application PID optimization. Prove method can solve problem algorithms falling into local optima due improper selection, crossover, methods, cannot effectively motor speed. Finally, Matlab2018a simulation compare with show values achieve oscillation, overshoot, faster target