The bearingless induction motor (BLIM) is a multi-variable, non-linear, strong coupling system. To achieve higher performance control, a novel neural network inverse system decoupling control strategy considering stator current dynamics is proposed. Taking the stator current dynamics of the torque windings into account, the state equations of the BLIM system is established first. Then, the inverse system model of the BLIM is identified by a three-layer neural network; by means of the neural network inverse system method, the BLIM system is decoupled into four independent second-order linear subsystems, include a rotor flux subsystem, a motor speed subsystem and two radial displacement component subsystems. On this basis, the neural network inverse decoupling control system is constructed, the simulation verification and analyses are performed. From the simulation results, it is clear that when the proposed decoupling control strategy is adopted, not only can the dynamic decoupling control between relevant variables be achieved, but the control system has a stronger anti-load disturbance ability, smaller overshoot and better tracking performance.

Bearingless induction motor (BLIM), is a nonlinear, multivariable and strongly coupled object. In order to improve its dynamic decoupling control performance, and overcome the influences of the load disturbance and the motor parameter variation, under the conditions of considering the stator current dynamics of the torque system, the inverse system model of BLIM system is established firstly, and by the inverse system method, the BLIM system is decoupled into four second-order pseudo linear subsystems. And then, according to the sliding mode control (SMC) theory, the SMC regulator is designed for each subsystem, an exponential approach law is used to reduce the chattering of SMC system; the stability of SMC system is verified by the Lyapunov method. Simulation experimental results have shown that the inverse system decoupling SMC system not only has an excellent dynamic decoupling control performance, but also has a faster response speed and a stronger robustness.

A bearingless induction motor is a multivariable, nonlinear and strong coupling object. To achieve its dynamic decoupling control with high performance and improve the system stability, a sliding mode variable structure (SMVS) control strategy based on inverse system decoupling is proposed. First, taking the stator current as the control variable, by means of inverse system method, the bearingless induction motor system is decoupled into four pseudolinear subsystems, including motor speed subsystem, rotor flux‐linkage subsystem and two radial displacement component subsystems. Then, according to the SMVS control theory, the regulator is designed for each subsystem. To overcome the chattering problem of the system, an exponential reaching law is introduced to the SMVS regulator; based on Lyapunov theory, system stability is analyzed. From the simulation experimental results, it is clear that the system has better dynamic decoupling control performance, a stronger ability to resist load disturbance and stronger robustness to the variation of motor parameters. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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Three-phase bearingless induction motor is a multivariable, nonlinear and strong coupling object, to achieve its decoupling control with high performance, an inverse system decoupling control strategy based on air gap flux orientation is proposed. Under the conditions of air gap flux orientation of torque system, the stator currents of torque winding and suspension winding are taken as input variables, and the inverse system mathematical model of bearingless induction motor is established; adopting the inverse system method, the bearingless induction motor is decoupled into four pseudo linear subsystems, include motor speed first-order integral subsystem, air gap flux-linkage first-order integral subsystem, α and β displacement components second-order integral subsystems. The structure of decoupling control system is presented also. From the simulation results, it is clear that not only the air gap flux-linkage of torque system can be controlled accurately and directly, but also the dynamic decoupling control between motor speed, air gap flux-linkage of torque system and two radial displacement components can be achieved; Meanwhile, the control system has the characteristics of small overshoot and fast response speed.