针对分数阶PID(proportion integration differentiation)控制器参数整定难的问题,本文提出改进的灰狼优化算法(improved grey wolf optimizer,IGWO)对分数阶PID控制器进行参数整定的方法.IGWO算法采用lo-gistic映射来初始化种群位置,提高种群的多样性,采用非线性收敛因子,增强全局搜索能力和局部开发能力,采用动态权重策略,根据适应度值调整α、β、δ狼的权重.为验证IGWO算法的有效性选取4个基准测试函数进行寻优和对2个经典被控系统进行控制器设计,并与传统灰狼算法、粒子群算法、遗传算法和粒子群结合灰狼算法进行对比分析,结果显示,在寻优测试中IGWO算法在收敛速度和解的精度上更有优势,采用IGWO算法设计得到的控制器的控制性能更好.
Improved Gray Wolf Optimization Algorithm for Fractional Order PID Controller Parameter Tuning
Aiming at the difficulty of parameter tuning of fractional order PID controller,this paper presents an im-proved Grey Wolf optimization algorithm(IGWO)for parameter tuning of fractional order PID controller.The IGWO algorithm uses logistic mapping to initialize the population position and improve the diversity of the population.It uses a nonlinear convergence factor to enhance the global search ability and local exploitation ability.It adopts a dynamic weighting strategy and adjusts the weights of α,β and δ Wolf according to the fitness value.In order to verify the effec-tiveness of IGWO algorithm,four benchmark test functions are selected for optimization and controller design of two classical controlled systems,and compared with traditional Grey Wolf algorithm,particle swarm algorithm,genetic algorithm and particle swarm combined Grey Wolf algorithm,the results show that,In the optimization test,IGWO al-gorithm has more advantages in convergence speed and precision,and the controller designed by IGWO algorithm has better control performance.
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