Application of neural-fuzzy modeling and optimal fuzzy controller for nonlinear magnetic bearing systems

Abstract

In this paper we apply a new approach, called optimal fizzy control based on linear TS type fuzzy model, to deal with nonlinear magnetic bearing systems. The linear TS type fuzzy model is used to represent the nonlinear plant To obtain the linear TS fuzzy model, we use linear self-constructing neural fuzzy inference network(linear SONFIN) to model the nonlinear system. Once the TS fuzzy model of the magnetic bearing system is obtained, the optimal fuzzy controller can be applied if the system is completely controllable and observable. Simulation results show that the proposed optimal fuzzy controller can operate in widely range of shaft position.