Optimization of Fractional and Integer Order PID Parameters using Big Bang Big Crunch and Genetic Algorithms for a MAGLEV System

This paper presents a study on optimized control for a magnetically levitated (MAGLEV) suspension system. Unstable magnetically levitated system is modelled and integer order PID (IOPID) and fractional order PID (FOPID) controller parameters are evaluated by using both Genetic Algorithm (GA) and Big Bang Big Crunch (BBBC) algorithm. Comparison between BBBC and GA based controllers are done. Responses for variable reference inputs are obtained. Results show that the performance of the BBBC based FOPID controller is better than GA optimized FOPID controller.