摘要
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。
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.
作者
任久斌
曹中清
REN Jiubin;CAO Zhongqing(College of Mechanical Engineering,Southwest Jiaotong University,Chengdu 610031)
出处
《计算机与数字工程》
2021年第1期94-98,共5页
Computer & Digital Engineering
基金
国家自然科学基金项目“多因素复合运动条件下金基合金摩擦副导电特性研究”(编号:U1730131)资助。
关键词
风驱动优化算法
多种群
协同搜索
PID控制器
参数整定
wind driven optimization algorithm
multiple population
collaborative search
PID controller
parameter tuning
