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

被引：4
|
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
收藏
页数：8
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