Optimal Tuning of PID Parameters for Magnetic Ball Levitation System Using Multi-objective Evolutionary Algorithms

In this work, a PID controller tuned with the multi-objective optimization is used to realize high precision tracking control of a magnetic levitation system. For the multi-objective optimization, a cost function based on the system dynamic response criteria is proposed. The weights of the multi-objective cost function are calculated by three different optimization algorithms: PSO, ABC, and GWO. Time domain performance of the system response obtained by the simulations for these three controller are compared. In addition, the performance of the obtained controllers is examined for a different reference signal and even under the disturbance.