PERFORMANCE ANALYSIS OF MAGNETIC LEVITATION SYSTEM USING DIFFERENT CONTROL ALGORITHMS

Abstract

This research work aims to control and stabilize the Magnetic Levitation system, which levitates a magnetic ball in space being under the influence of a magnetic field only. Magnetic Levitation is a keen area of research as it reduces cost of maintenance and increases its efficiency. It has numerous applications in industries. To name a few of the applications, transportation and low friction bearings are some. Different controllers are used to stabilize the highly unstable nature of the maglev system. The transfer function is constructed through dynamic model analysis, which is then applied to a more straightforward mathematical model. Different controllers used are PD, PID and PID plus double derivative. Various time domain parameters like Settling time, Peak time, Rise time, and Maximum Overshoot are computed and compared with differently tuned PID gain values which are calculated after applying optimization algorithms. The applied algorithms for optimization are Genetic Algorithm, Particle Swarm Optimization, Giza Pyramids Construction and Honey Badger Algorithm. The applied algorithms are found to be helpful in reaching a steady state at a faster rate with less steady state error.