Application of Control Parameters Optimization of CNC Servo System Based on Self-Adaptive Genetic Algorithm
In order to solve the shortcomings of current engineering methods for parameters adjustment that can only deal with them according to single requirement of system and can not optimize them in the whole range, as well as the standard genetic algorithm is prone to premature convergence, therefore, an improved PID parameters adjustment method based on self-adaptive genetic algorithm was proposed. This approach enables crossover and mutation probability automatically change along with the fitness value, not only can it maintain the population diversity, but also can ensure the convergence of the algorithm. A comparison of the dynamic response between the traditional PID control and the PID control based on self-adaptive genetic algorithm was made. Simulation results show that the latter has much superiority.
Zhong Cao, Xueqiang Cao, Lixian Sun, Yinghe He
G. R. Dong and P. B. Zhao, "Application of Control Parameters Optimization of CNC Servo System Based on Self-Adaptive Genetic Algorithm", Advanced Materials Research, Vols. 239-242, pp. 2847-2850, 2011