Direct Torque Control System Of Induction Motor Based On Advanced Algorithms

The paper entirely summarizes the actuality and development of Direct Torque Control (DTC) of the induction motors, and then the author made a study of asynchronous motor and DTC. Compared with Vector Control, the main advantage of DTC is that it directly controls flux and torque. The paper analyses the mathematical model and shows that the key of DTC is to select the right stator voltage vectors due to the stator flux and torque. The function of voltage vectors on the stator flux and torque is investigated.In order to enhance the control performance of DTC much more, fuzzy neural network control algorithm is adopted. The DTC system based on Fuzzy Neural Network is designed. In this Fuzzy Neural Network, Fuzzy Logic is combined with artificial Neural Network in series. It has the characteristic of self-learning, self-adjusting and parallel processing. It is very easy to realize this Fuzzy Neural Network. In order to approve the validity of this control strategy, the Simulation model of the DTC system based on Fuzzy Neural Network Control are built in MATLAB/SIMULINK. The result of the simulation indicate that the control performance of the DTC system based on Fuzzy Neural Network is enhanced evidently compared with the conventional DTC system, especially the torque ripple and flux ripple are diminished evidently. It provides a feasible scheme for developing the DTC system and the other AC drive system which have high control performance.In addition, the TMS320F240 chip is used as the core-processing control. The other circuits contain the signal gathers, rectification, Intelligent Power Module(IPM), drive and protect and so on. The experiment proves that the control design is effective.