Parameters Optimization Method for Human-Simulated Intelligent Controller Based on Immune Theory

摘要

To solve the problems of parametric optimization for human simulated intelligent controller (HSIC) in complicated controlled plant. Inspired by biology immune system, the paper presents a novel parameter optimization method for HSIC based on immune theory, which is termed as IHSIC. Firstly, the design process of HSIC controller have been discussed, secondly, antibody, antigen and affinity of the parameter optimization problem were defined, then, the process of parameter tuning based on immune principles was discussed in detail. The simulation experiments show that the control effect of IHSIC is much better than proportional-integral-derivative (PID) controller, and it is suitable to solve the puzzle of complicated controlled plant.