基于改进鲸鱼优化算法的分数阶PID参数整定  

Fractional Order PID Parameter Tuning Based on Improved Whale Optimization Algorithm

作　　者：张艳丽 陆琦 ZHANG Yanli;LU Qi(Panjin Institute of Industrial Technology,Dalian University of Technology,Panjin 124221,China;Dandong Dongfang Measurement and Control Technology Co.,Ltd.,Dandong 118000,China)

机构地区：[1]大连理工大学盘锦产业技术研究院,盘锦124221 [2]丹东东方测控技术股份有限公司,丹东118000

出　　处：《自动化与仪表》2024年第8期127-131,153,共6页Automation & Instrumentation

基　　金：辽宁省化学助剂合成与分离省市共建重点实验室资助项目(ZJKF2101)。

摘　　要：该文提出了一种自适应混合策略鲸鱼优化算法(adaptive mixed strategy whale optimization algorithm,AMSWOA)用于分数阶PID控制器的参数整定。该算法基于鲸鱼优化算法进行改进,引入Tent混沌序列用以提高WOA的种群多样性、全局搜索能力和收敛速度;同时,采用了收敛因子非线性变化策略,并引入自适应权重以克服算法陷入局部最优解的问题;高斯变异的加入则有助于提高算法的搜索精度和寻优性能。通过在MATLAB/Simulink环境下验证整数阶和分数阶系统的被控对象,并与鲸鱼算法、灰狼优化算法及粒子群优化算法进行比较,证实了该文的AMSWOA算法对求解分数阶PID控制器参数整定问题的有效性和实用性。According to the design problem of fractional order PID controller,adaptive mixed strategy whale optimization algorithm(AMSWOA)is proposed to adjust the parameters of fractional order PID controller.The tent chaotic sequence is introduced into whale optimization algorithm(WOA)to improve the population diversity global search ability and convergence speed of WOA.The nonlinear variation strategy of convergence factor is used,and adaptive weight is added to solve the problem that the algorithm falls into the local optimal solution.The addition of Gaussian mutation helps to improve the search accuracy and optimization performance of the algorithm.By verifying the controlled objects of the integer-order and fractional-order in the MATLAB/Simulink,the results that compared with WOA algorithm,grey Wolf optimization algorithm and the particle swarm optimization algorithm,the effectiveness and practicability of AMSWOA in this paper for solving fractional order PID controller parameter tuning problem are verified.

关 键 词：自适应混合策略鲸鱼优化算法 分数阶PID控制器 Tent混沌 高斯变异 鲸鱼优化算法 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]