Optimum PID Controller Tuning Using Soft computing Methodologies for Industrial Process

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 of a various plant by selection of PID parameters using soft computing techniques. Z-N methods whose performance have been compared and analyzed with the intelligent tuning techniques like Genetic algorithm, Evolutionary programming and particle swarm optimization. Soft computing methods have proved their excellence in giving better results by improving the steady state characteristics and performance indices.