基于多种群风驱动优化算法的PID参数整定

针对标准风驱动优化算法容易收敛到局部最优和未成熟收敛的问题,提出了一种多种群风驱动优化算法,并将其用于PID控制器的参数整定。该算法将PID控制器的比例、积分和微分参数作为空气微团的位置矢量,以ITAE指标作为算法的适应度函数,通过多个种群协同搜索,寻求解空间中适应度值最小的位置。通过实验仿真,并与基于标准风驱动优化算法、基于遗传算法和基于粒子群算法的PID参数整定相比,该算法在收敛速度、收敛精度等方面均表现出更好的性能。

Parameters Tuning of PID Based on Multi-population Wind Driven Optimization Algorithm

Aiming at the problem that the standard wind driven optimization algorithm is easy to converge to local optimum and immature convergence,a multi-population wind driven optimization algorithm is proposed and used for parameter tuning of PID controller.The algorithm uses the proportional,integral and differential parameters of the PID controller as the position vector of the air micelle,and uses the ITAE index as the fitness function of the algorithm.Through the collaborative search of multiple popula?tions,the location of the solution with the smallest fitness value is sought.Compared with the PID parameter tuning based on stan?dard wind driven optimization algorithm,genetic algorithm and particle swarm optimization algorithm,the algorithm has better per?formance in terms of convergence speed and convergence precision.