基于改进PSO的原动机仿真系统PI参数优化

Optimizing PI Parameters in Prime Mover Simulation System Based on Improved Particle Swarm Optimization Algorithm

原动机仿真系统中的速度电流综合调节器实质为PI调节器,其比例系数kP和时间常数τL依靠传统方法难以确定。针对此问题,提出一种改进的粒子群优化算法,以ITAE指标作为改进PSO优化算法的适应度函数。通过具体实例,运用MATLAB仿真试验,比较分析传统方法、免疫遗传算法和改进粒子群算法的控制效果。试验结果表明:改进的PSO优化算法简单实用,并可显著提高原动机仿真系统的动态特性。

In the prime mover simulation system,parameters of the PI regulator,such as ratio coefficient kP and time constantτL,are difficult to be determined by the traditional methods.To solve this problem,this paper proposed an improved PSO algorithm with the ITAE criterion of speed errors as the fitness function of the improved PSO algorithm.By using the specific example and the MATLAB simulation,the traditional method,the immune genetic algorithm and the improved particle swarm control were compared.The results showed that the improved PSO algorithm can easily and accurately find the optimal PI parameters,and significantly enhance the enable the dynamic characteristic of prime mover simulation system.