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

Abstract

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

CLC Number:

TP273

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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References 12

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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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Fuzzy PID control of ultrasonic motor based on improved quantum genetic algorithm

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