| one method of AC induction motor control called Direct Torque Control (DTC),which was raised in 1970's .has been developed rapidly in the middle of 1980's and is a powerful control method for motor drives. Following the vector control technique, the quick development of DTC makes itself a new high performance AC driving technique paralleling to the vector control. Now the technique in AC driving is studied widely. In this thesis the author made a study of technique.To fulfill high performance direct torque control of an induction motor, it is necessary to know precisely parameters of induction motor, such as rotor speed and stator resistance. So wavelets and neural network are combined and wavelet neural network (WNN) is proposed. Through WNN identifier, stator resistance and rotor speed are identified. In this paper, wavelet neural network configuration is expatiated and its algorithm is analyzed. At last conjugate gradient method and orthogonal least squares algorithm and on-linear identification recursive orthogonal least squares algorithm are proposed.According to induction motor principle, simulation model of direct torque control system with wavelet neural network identifier is built. Simulation result reveals that DTC system with WNN identifier showed excellent static and dynamic performance. So through using speed identifier with WNN replacing speed sensor on the DTC system, the scheme with no speed sensor is effective and feasible, and direct torque control system with WNN stator resistance detector resolved low speed performanceFinally. We developed a hardware system based on Digital Signal Processor (DSP), and to the system can run steadily, we designed the scheme of direct torque control and study the PWM method controlled by the hexagon flux trace.According to this paper, we can believe that the combination of wavelet transform and neural network will advance the development of intelligent control science and detection technology.
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