Experimental evaluations of proportional-integral-derivative type fuzzy controllers with parameter adaptive methods for an active magnetic bearing system

This paper deals with the experimental control of a rotating active magnetic bearing (AMB) system using proportional-integral-derivative type fuzzy controllers (PIDFCs) with parameter adaptive methods. Three kinds of parameter adaptive method, including fuzzy tuner, function tuner and relative rate observer, have been proposed in the literature for tuning the coefficients of PIDFCs. However, only a simulation comparison between these methods for control of a second-order linear system with varying parameters and time delay has been done. In general, theoretical models need to be confirmed and modified through experimental results. This paper provides experimental verification by applying PIDFCs with self-tuning algorithms for control of a highly nonlinear AMB system. It is shown that the steady-state error of the AMB system using the function tuner method is lower and the first resonant frequency of the AMB system using the relative rate observer method is higher than the other two methods, and the proportional-integral-derivative controller is quite unstable. The experimental results also show that all of the tuning methods can support a high rotation frequency of the AMB system. In practice, there are only a few differences between the three kinds of parameter adaptive methods.