基于改进量子遗传算法的超声电机模糊PID控制

doi:10.13229/j.cnki.jdxbgxb20200659

摘要/Abstract

摘要：

针对超声电机非线性、时变性的特点，设计了模糊自整定PID控制器，并利用量子遗传算法对模糊自整定PID控制器参数进行优化，以提高系统的动态性能和适应性。针对传统量子遗传算法的不足，对编码方式、种群初始化、量子旋转门、量子变异以及增加量子灾变5个方面进行改进。仿真结果表明：改进量子遗传算法改善了传统量子遗传算法容易产生种群早熟的问题，提高了算法收敛性能。同时，基于改进量子遗传算法的模糊自整定PID控制器与经典的模糊自整定PID控制器相比，明显提高了超声电机系统的动态和稳态性能。

关键词: 控制理论与控制工程, 超声电机, 模糊PID控制, 改进量子遗传算法

Abstract:

Aiming at the problem of the nonlinear and time-varying characteristics of ultrasonic motor, a fuzzy self-tuning PID controller is designed, and the parameters of the fuzzy self-tuning PID controller are optimized by using an improved quantum genetic algorithm, which can improve the dynamic performance and adaptability of the system. In order to overcome the shortcomings of traditional quantum genetic algorithm, five improving measures are taken, including the coding mode, population initialization, quantum rotation gate, quantum mutation and adding quantum catastrophe. The simulation results show that the improved quantum genetic algorithm can improve the convergence performance and the premature population problem of traditional quantum genetic algorithm. At the same time, the fuzzy self-tuning PID controller based on the improved quantum genetic algorithm significantly improves the dynamic and stable state performance of the ultrasonic motor system compared with the classical fuzzy self-tuning PID controller.

Key words: control theory and control engineering, ultrasonic moto, fuzzy PID controller, improved quantum genetic algorithm

中图分类号:

TP273

冯建鑫,王强,王雅雷,胥彪. 基于改进量子遗传算法的超声电机模糊PID控制[J]. 吉林大学学报(工学版), 2021, 51(6): 1990-1996.

Jian-xin FENG,Qiang WANG,Ya-lei WANG,Biao XU. Fuzzy PID control of ultrasonic motor based on improved quantum genetic algorithm[J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(6): 1990-1996.

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算法	优化参数名称					性能指标
算法	e	ec	ΔK_P	ΔK_I	ΔK_D	性能指标
IQGA	0.0273	0.001 370	0.016 60	6.72	0.003 32	45.08
QGA	0.0262	0.000 732	0.003 67	5.82	0.002 15	46.93

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