Application of Fuzzy Immune Algorithm and Soft Computing in the Design of 2-DOF PID Controller - Ning Ding; Priti Prabhakar; Anita Khosla; Vishal Jagota; Edwin Ramirez-Asis; Bhupesh Kumar Singh (Discrete Dynamics in Nature and Society)
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.