The Application of Immune Genetic Algorithm in PID Parameter Optimization for Level Control System

This work discusses the use of an Evolvable Proportional-Integral-Derivative (PID) controller that consists of an evolvable PID controller hardware whose gains can be set by Evolutionary Computation techniques, such as Genetic Algorithms in water level control system. Due to PID controllers´ widespread use in industry, tuning procedures for them are always a topic of interest. An evolutionary immune inspired algorithm, named Immune Genetic Algorithm (IGA), is used for tuning the controller so that closed-loop step response specifications are satisfied. Experiments with different processes indicate that the gains obtained through Immune Genetic Algorithm (IGA) may provide better responses than those obtained by the classical Ziegler-Nichols method. The PID Controller based on IGA is realized by the configuration software and Lab VIEW. The experiment results show that the water level controlled by the PID controller can response fast and reach the stable state quickly in comparison with that controlled by the conventional PID controller.