Studying On PID Control With Parameters Optimization Based On Immune Genetic Algorithms

PID control is the most common control method used in process control because of its single algorithm, good robustness and high reliability. Sometimes it is difficult to establish the precise mathematical model in practice, as industry process has non-linearity and time-variety uncertainty. So it cannot attain perfect control effect to use the general PID controller in industry process. Aiming at these questions, people continuously research the methods, which can tune the parameters of the PID controller adapting complex industry status and more exact control demands. Although there are many advantages in using PID control, it is difficult to robustly tune the parameters. Therefore, many specialists and scholars begin to study some optimal algorithms to tune PID control parameters, such as the adaptive intelligent controller, the neural net controller, the genetic algorithm controller, etc. The traditional genetic algorithms have a set of quite perfect algorithm system and have been applied in many optimization problems successfully. But there are still some drawbacks, such as lack of local search ability, premature convergence, random walking, etc., which lead to the bad performance in convergence. Recently the studies on biology show that the immune action can hamper the premature and effectively speed up the optimizing. Therefore, the immune principle can give us important edification on how to enhance the performance in the traditional genetic algorithms. This dissertation propose a novel and effective optimization algorithm of PID controller parameters based on Immune Genetic Algorithm (IGA) over the analysis of the drawbacks of traditional GA's and the existing immune theories. This dissertation aims to make the designed algorithm effectively resolve the contradiction between local and global search capability and keep the population diversity during the evolving progress so as to remedy the demerits of traditional GA's. Meanwhile, the experiments on the typical object show that the PID controller based on IGA can accelerate the speed of response and decrease the overshoot. It also has good performance against interfere for parameter variation and good robustness. Additionally, PID multivariate controller based on IGA is proposed in this dissertation. This method of optimizing multivariate coupling system is a new way to obtain satisfactory dynamic control effect.