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Artificial neural networks inverse control of 5 degrees of freedom bearingless induction motor
by Xiaodong Sun; Huangqiu Zhu
International Journal of Modelling, Identification and Control (IJMIC), Vol. 15, No. 3, 2012

 

Abstract: A decoupling control approach based on artificial neural networks (ANN) inverse system method has been developed for the innovative 5 degrees of freedom (DOF) bearingless induction motor, which is multi-variable, non-linear and coupled system. The working principles of 3 DOF magnetic bearing and 2 DOF bearingless induction motor are analysed, and then the mathematical model of 5 DOF bearingless induction motor is given. The reversibility of the model is proved. Combining the ANN inverse system with the 5 DOF bearingless induction motor, the system is decoupled into five independent 2-order linear displacement subsystems, a 1-order linear speed subsystem and a 1-order linear magnetic linkage subsystem. The design of outer loop controller is easier, so the whole system control performance is further improved. In the end, the system is implemented on Matlab7.0/Simulink. The simulation results have showed that this kind of control strategy can realise dynamic decoupling control between torque force and radial suspension forces, and the control system has fine dynamic and static performance.

 

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