Affined-type Neural-Fuzzy Gap Control of Electromagnetic Suspension Systems

Electromagnetic suspension (EMS) systems are highly nonlinear, especially for current-controlled EMS, which is not only nonlinear to system states abut also to system inputs. And hence, theoretically approach to derive T-S fuzzy system is unsuitable. In this work, we use self-organizing neural-fuzzy technique to obtain affine-TS fuzzy models for both voltage-and current-controlled EMS systems. Based on these two models, affine-type optimal fuzzy controls for these two highly nonlinear systems are derived. The control performance and robustness to external disturbance are demonstrated and are compared with linear type. Since affine T-S fuzzy model can provide one more adjustable parameter for neural-fuzzy modelling, the derived affine TS-based controller could have better performance than linear type as system complexity increases. This phenomena obviously exists in simulation for current-controlled EMS systems