Nonlinear decoupling control for 5 degrees-of-freedom bearingless permanent magnet synchronous motor

Abstract

A innovative 5 degrees-of-freedom (DOF) bearingless permanent magnet synchronous motor (BPMSM) is a multi-variable, nonlinear and strong-coupled system. In order to achieve rotor suspension and operation steadily, it is necessary to realize dynamic decoupling control among torque and suspension forces. A decoupling control approach based on artificial neural networks(ANN) inverse system method has been developed for the 5 DOF BPMSM. The mathematic model of 5 DOF BPMSM is given. The model is analyzed with reversibility and proved to be reversible. Combining the ANN inverse system with the 5 DOF BPMSM, the system is decoupled into five independent 2-order linear displacement subsystems and a linear 1-order speed subsystem. The servo robust controller is used to design linear closed-loop controller. The experiment results have shown that the strong robustness, the good static and dynamic decoupling performance can be achieved by using the proposed method for a 5 DOF BPMSM.