Title :
Direct torque control of three-level inverter using neural networks as switching vector selector
Author :
Wu, Xuezhi ; Huang, Lipei
Author_Institution :
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
Abstract :
In this paper, based on the detailed study on the characteristic of direct torque control (DTC) and output vector of the three-level inverter, a simplified method to choose the output vector for DTC of the three-level inverter fed induction motor is proposed. A novel switching vector selector using the ANN (artificial neural network) is trained under the tutor of the method mentioned above. By the usage of the ANN, when the error of the torque and stator flux is made certain, the output vector can be expediently acquired. The validity of the proposed vector selector is confirmed by the simulative results.
Keywords :
induction motor drives; invertors; learning (artificial intelligence); machine control; neural nets; stators; switching circuits; torque control; artificial neural network; direct torque control; neural networks; output vector; stator flux; switching vector selector; three-level inverter; three-level inverter fed induction motor; torque error; Artificial neural networks; Capacitors; Control systems; Electromagnetic interference; Neural networks; Pulse width modulation; Pulse width modulation inverters; Stators; Torque control; Voltage;
Conference_Titel :
Industry Applications Conference, 2001. Thirty-Sixth IAS Annual Meeting. Conference Record of the 2001 IEEE
Conference_Location :
Chicago, IL, USA
Print_ISBN :
0-7803-7114-3
DOI :
10.1109/IAS.2001.955565