Genetic Algorithm and Fuzzy Adaptive PI Controller on DTC of Induction Motor

         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 on-line to optimize the fuzzy PI controller, is proposed. In this approach, according to speed error and its first-time derivative, the proportional coefficient Kp and integral coefficient Ki can be on-line adjusted by fuzzy adaptive PI speed regulation, and the fuzzy logic adapter parameters are optimized by genetic algorithm to improve the self-adaptation 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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