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

Author:

Ding Ning1ORCID,Prabhakar Priti2ORCID,Khosla Anita3ORCID,Jagota Vishal4ORCID,Ramirez-Asis Edwin5ORCID,Singh Bhupesh Kumar6ORCID

Affiliation:

1. School of Artificial Intelligence, Zhengzhou Railway Vocational & Technical College, Zhengzhou 450052, China

2. Electrical Engineering Department, Guru Jambeshwar University of Science and Technology, Hisar, India

3. EEE Department, Faculty of Engineering and Technology, Manav Rachna International Institute of Research and Studies, Faridabad, India

4. Department of Mechanical Engineering, Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh, India

5. Universidad Nacional Santiago Antunez de Mayolo, Huaraz, Peru

6. Arba Minch Institute of Technology, Arba Minch University, Arba Minch, Ethiopia

Abstract

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.

Publisher

Hindawi Limited

Subject

Modeling and Simulation

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