SOFT COMPUTING BASED CONTROLLERS FOR ELECTRIC DRIVES - A COMPARATIVE APPROACH

ABSTRACT PID controllers are widely used in industrial plants because it is simple and robust. Industrial processes are subjected to variation in parameters and parameter perturbations, which when significant makes the system unstable. The aim of this paper is to design a controller for applications of various electric drives in industry by selection of PID parameters using soft computing techniques. Performance of Z-N methods have been compared and analyzed with the intelligent tuning techniques like Genetic algorithm, Evolutionary Programming, Particle Swarm Optimization and Bacterial Foraging Optimization. Soft computing methods have proved their excellence in giving better results by improving the steady state characteristics and performance indices