Adaptive nonsingular terminal sliding model control of the suspension system for a bearingless permanent magnet synchronous motor

To improve the stability and disturbance rejection for the suspension system of a bearingless permanent magnet synchronous motor (BPMSM), an adaptive nonsingular terminal sliding mode (NTSM)control is proposed in suspension system. Radial basis function neural network(RBFNN) is introduced to estimate the upper bound of the uncertainties, and faster convergence speed of system state variables can be obtained during the whole process. The suspension control system for the bearingless motor with rotor flux orientation is also implemented on the basis of proposed controller. Simulation results show that the proposed method is effective, higher robustness in disturbances is achieved.