This project is design based on the paper "Research on Direct Torque Control of Induction Motor Based on Genetic Algorithm and Fuzzy Adaptive PI Controller". In this project, a comparative study between adaptive fuzzy PI direct torque control and fuzzy GA. A novel direct torque control strategy, using genetic algorithm online to optimize the fuzzy PI controller, is proposed. In this approach, according to speed error and its firsttime derivative, the proportional coefficient Kp and integral coefficient Ki can be online adjusted by fuzzy adaptive PI speed regulation, and the fuzzy logic adapter parameters are optimized by genetic algorithm to improve the selfadaptation of speed. Moreover, the second fuzzy logic controller is applied to select the voltage vector instead of the conventional hysteresis controllers. Fuzzy PI direct torque control and proposed approach show that not only the speed response, overshoot and speed steady precision have been improved, but also the torque, flux, and stator current ripples have been effectively decreased at low speed, and the robustness of the whole system has been enhanced. Reference Paper: Research on Direct Torque Control of Induction Motor Based on Genetic Algorithm and Fuzzy Adaptive PI Controller Author’s Name: Hao Li, Qiuyun Mo, and Zhilin Zhao Source: International Conference on Measuring Technology and Mechatronics Automation Year:2010
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