Inverse System Decoupling Control for Induction Motor Based on Neural Network On-line Learning
The induction motor is a MIMO, nonlinear and high coupling system. The reversibility of the induction motor is testified. Consequently, a pseudo-linear system is completed by constructing a neural network inverse (NNI) system and combining it with the motor system. The inverse can transform the MIMO nonlinear system into two SISO linear subsystems (i.e., rotor speed and flux subsystems). In order to approach the inversion exactly in operation of the motor, the control method online learning based on NNI system is proposed, in which connection value can be amended continuously on-line to make the NN adapt to the changes of environment to strengthen its robustness. Simulation and experiment results have shown that NN can be adjusted in the control process. The good applicability of NN along with the strong stability and robustness of the system can be achieved by using the proposed method.
neural network inverse system on-line learning induction motor
Ni Wei Zhang Yu
Department of Electronic and lnformation Engineering Huaiyin Institute of Technology Huaian,China Department of Computer and Information Engineering Huaiyin Institute of Technology Huaian,China
国际会议
长沙
英文
1576-1579
2009-04-11（万方平台首次上网日期，不代表论文的发表时间）