基于GA-PSO融合算法的二自由度PID参数优化

doi:10.16180/j.cnki.issn1007-7820.2019.10.011

Abstract

Abstract:

In industrial process control systems, the tuning of PID parameters have direct influence on the quality and efficiency of production. Aiming at the difficulty of PID parameter adjustment, an intelligent fusion algorithm combined with genetic algorithm and particle swarm optimization was proposed, and the proposed algorithm was applied to tuning parameters of two-degree-of-freedom PID controller. The algorithm introduced particle swarm optimization algorithm into the mutation operator of genetic algorithm, which fully exploited the advantages of two single intelligent algorithms and made up for the shortcomings of both. The simulation results showed that the proposed algorithm could be applied to tuning PID parameters and excellent performance index values in the process of adjusting the PID parameters. Moreover, it had better control effects on target value tracking characteristics and external disturbance suppression characteristics.

Key words: genetic algorithm, particle swarm optimization, two degrees of freedom, mutation operator, intelligent algorithm, parameter optimization, performance index

CLC Number:

TP273

WU Yankai,ZHANG Wei,MA Yingman,LI Jiayang. Two Degree of Freedom PID Parameter Optimization Based on GA-PSO Fusion Algorithm[J].Electronic Science and Technology, 2019, 32(10): 54-59.

Figures/Tables 7

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Table 1

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Table 2

References 17

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参数	目标值跟踪特性		外扰动抑制特性
参数	K_c₁	T_d₁	K_c₂	T_i₂	T_d₂
GA-PSO	2.083 0	1.000 0	10.000 0	0.996 8	0.503 9
文献[7]	3.292 6	0.703 7	3.850 6	2.275 1	0.571 2
文献[8]	2.851 6	0.847 7	7.187 5	1.025 1	0.625 0
文献[9]	2.204 7	1.000 0	6.630 6	0.873 9	1.000 0

调节方法	目标值跟踪特性			外扰动抑制特性
调节方法	IAE	ISE	t_s	IAE	ISE	t_s
GA-PSO	0.483	0.335	0.790	0.116	0.007	1.320
文献[7]	0.642	0.423	0.750	0.591	0.097	4.070
文献[8]	0.557	0.371	0.760	0.189	0.014	2.140
文献[9]	0.501	0.356	0.780	0.227	0.013	2.510

Two Degree of Freedom PID Parameter Optimization Based on GA-PSO Fusion Algorithm

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