The Research Of Induction Motor Vector Control System Based On Wavelet Neural Network

The field oriented control technique is widely used in high performance motion control of induction motors. However, in real-time implementation,precise decoupling which requires accurate motor parameter can't be fully realized due to significant plant uncertainties such as external disturbances, parameter variations and plant nonlinear dynamics. This may deteriorate the dynamic performances of flux and torque significantly.To fulfill high performance vector control of an induction motor, it is necessary to know precisely parameters of induction motor,such as rotor speed and Rotor magnetism chain. So wavelets and neural network are combined and wavelet neural network (WNN) is proposed. Through WNN identifier, Rotor magnetism chain and rotor speed are identified. In this paper, wavelet neural network configuration is expatiated and its algorithm is analyzed.According to induction motor principle,simulation model of vector control system with wavelet neural network identifier is built. Simulation result reveals that vector control system with WNN identifier showed excellent static and dynamic performance. So through using speed identifier with WNN replacing speed sensor on the vector control system,the scheme with no speed sensor is effective and feasible, and vector control system with WNN stator resistance detector resolved low speed performance.Finally, We developed a system based on Digital signal processor (DSP), and to the system can run steadily, we designed the scheme of vector control and study the PWM method controlled by the hexagon flux trace.According to this Paper's research , we can believe that the combination of wavelet transform and neural network will advance the development of intelligent control science and detection technology.