Nonlinear Model Predictive Controller Performances Analysis for Magnetic Levitation System

Magnetic levitation system is nonlinear plant used to levitate object by using attraction force or repulsive force between magnetic force and ferromagnetic material.In this paper stability of Model Predictive Controller, under various constraints on inputs and outputs, has been analysed. The state estimation has been used to ensure the stability of the system. Since Model Predictive Controller is based on prediction theory in which input signal is computed at each sampling interval and output is estimated, so computed control signal at each sampling time is optimized over a specified horizon. The first calculated value of input signal is implemented and rests are discarded. Then this process is repeated for the next step. The Results show clearly that the conventional controller like PID and Fuzzy PID gets failed to control the system effectively under such variation on constrained, so an accurate model and complex algorithm are required to design a self-tuned Fuzzy PID controller to accommodate the ability to handle the constrained variation.

Keywords:

PID , PID Fuzzy , Predictive Controller , Magnetic Levitation System , state estimation , stability