Application of Fuzzy Immune Algorithm and Soft Computing in the Design of 2-DOF PID Controller

被引：6

作者：

Ding, Ning ^{[1
]}

Prabhakar, Priti ^{[2
]}

Khosla, Anita ^{[3
]}

Jagota, Vishal ^{[4
]}

Ramirez-Asis, Edwin ^{[5
]}

Singh, Bhupesh Kumar ^{[6
]}

机构：

[1] Zhengzhou Railway Vocat & Tech Coll, Sch Artificial Intelligence, Zhengzhou 450052, Peoples R China

[2] Guru Jambeshwar Univ Sci & Technol, Elect Engn Dept, Hisar, India

[3] Manav Rachna Int Inst Res & Studies, Fac Engn & Technol, EEE Dept, Faridabad, India

[4] Madanapalle Inst Technol & Sci, Dept Mech Engn, Madanapalle, Andhra Pradesh, India

[5] Univ Nacl Santiago Antunez Mayolo, Huaraz, Peru

[6] Arba Minch Univ, Arba Minch Inst Technol, Arba Minch, Ethiopia

来源：

DISCRETE DYNAMICS IN NATURE AND SOCIETY | 2022年 / 2022卷

关键词：

SYSTEM;

D O I：

10.1155/2022/5608054

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

To solve the difficulty in selecting the crossover probability and mutation probability in genetic algorithms, a fuzzy immune algorithm based on adaptive estimation of crossover probability and mutation probability in a fuzzy reasoning system is proposed, and it is used in the parameter optimization design of a two-degree-of-freedom PID controller. According to the experiment and simulation results, classic genetic algorithm evolution tends to halt after 37 generations, with a fitness value of 7.135, whereas fuzzy genetic algorithm evolution tends to stop after 20 generations, with a fitness value of 7.486. The 2-DOF PID controller that was created can give the system strong target value following and interference suppression features at the same time.

引用

页数：8

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