Inverse System Decoupling Control for Induction Motor Based on Neural Network On-Line Learning

Author(s):  
Wei Ni ◽  
Yu Zhang
2013 ◽  
Vol 433-435 ◽  
pp. 1154-1160
Author(s):  
Wen Shao Bu ◽  
Cong Lin Zu ◽  
Chun Xiao Lu ◽  
Xin Wen Niu

For the strong coupling problem of three-phase bearingless induction motor which is a multi- variable and nonlinear object, a kind of decoupling control strategy based on inverse system method is proposed. The reversibility of torque subsystem was analyzed based on rotor flux orientation, and the decoupling control strategy based on inverse system method was analyzed. Then the torque system was decoupled into two second-order linear subsystems, i.e. the rotor speed subsystems and the rotor flux subsystems. The suspension system adopts negative feedback control; the required air-gap flux linkage of torque system was obtained from the rotor flux and stator current. Finally, synthesis and simulation of the overall control system were researched. Simulation results demonstrate that good performance of decoupling control can be achieved. The presented control strategy is feasible and available.


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