粒子群算法自寻优模糊PID控制器设计  

Design of Self-optimizing Fuzzy-PID Controller with Particle Swarm Algorithm

作　　者：杨洋 张秋菊 YANG Yang;ZHANG Qiuju(School of Mechanical Engineering,Jiangnan University,Wuxi 214122,China;Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology,Wuxi 214122,China)

机构地区：[1]江南大学机械工程学院,江苏无锡214122 [2]江苏省食品先进制造装备技术重点实验室,江苏无锡214122

出　　处：《机械制造与自动化》2018年第3期201-204,共4页Machine Building & Automation

基　　金：江苏省重点研发计划-产业前瞻与共性关键技术项目(BE2015051)

摘　　要：针对常规模糊PID控制器的控制规则和控制参数固定不变而降低了系统自适应能力的问题,提出了一种基于粒子群算法寻优的方法对模糊控制器进行寻优。通过改变模糊控制器的3个尺度系数(K_e、K_(ec)、K_u),可以改变不同阶段系统的误差以及误差变化率所对应的权重。以ITAE指标作为粒子群寻优的目标函数,可以保证系统的快速响应性、超调量、调节时间以及稳态误差等。通过在Matlab下建立交流永磁同步电机(PMSM)模型,对其仿真分析表明:粒子群算法自寻优模糊PID控制器有着更优越的控制性能。Because of the fixed control parameters and control rules of the conventional fuzzy PID controller,the capacity of the self-adaptation is reduced. This paper proposes a new self-optimizing method,based on the particle swarm algorithm to optimize the fuzzy controller. By changing the three scale coefficients of the fuzzy controller（ K_e、K_（ec）、K_u）,the different stages of the system error and the error rate of the corresponding weight can be changed. The ITAE is used as the optimizing objective of particle swarm optimization,thus ensuring the system＇s quick response,overshoot,adjust able time and steady state error,etc. Through the model of the permanent magnet synchronous motor（ PMSM） eatablished in Matlab,its simulation analysis is done. The results show that the self-optimizing fuzzy PID controller with the particle swarm algorithm has better control performance.

关 键 词：模糊PID控制 粒子群算法 参数自寻优 

分 类 号：TP271[自动化与计算机技术—检测技术与自动化装置]