Multi-objective PID-controller tuning for a magnetic levitation system using NSGA-II

Abstract

This paper investigates the issue of PID-controller parameter tuning for a magnetic levitation system using the non-dominated sorting genetic algorithm (NSGA-II). The magnetic levitation system is inherently unstable and the PID-controller parameters are hard to find using conventional methods. Based on four different performance measures, derived from the step response of the levitation system, the algorithm is used to find a set of non-dominated parameters for a PID-controller that can stabilize the system and minimize the performance measures.