DocumentCode :
482576
Title :
Research and simulation on ANN speed-sensorless three-level inverter vector control system for induction motor
Author :
Jiang, Wei ; Feng, Xiao Yun ; Wang, Qing Yuan
Author_Institution :
Dept. of Electr. Eng., Southwest Jiao Tong Univ., Chengdu
fYear :
2008
fDate :
17-20 Oct. 2008
Firstpage :
1577
Lastpage :
1581
Abstract :
This paper presents a new speed-sensorless vector control drive system for induction motor. In order to produce low harmonics in output voltage and current, reduce the torque fluctuation, and avoid the high voltage jump in switching time, the system utilizes three-level inverter to supply power for the induction motor and a SVPWM scheme with neutral point voltage balance strategy is applied for the three-level inverter. The speed estimator in this system is constructed based on artificial neural network (ANN) theory. Compared with the conventional model reference adaptive system (MRAS) method realized dependent on the PI controller, ANN speed estimator uses the intelligent learning algorithm to complete the speed estimation so that a real-time identification of the motor speed is acquired precisely with excellent dynamic response in various conditions. This paper describes both the theoretical analysis as well as the simulation results to verify the effectiveness of this drive system.
Keywords :
PI control; angular velocity control; electric machine analysis computing; induction motor drives; invertors; learning (artificial intelligence); machine vector control; neural nets; ANN speed-sensorless control system; PI controller; artificial neural network theory; excellent dynamic response; induction motor; intelligent learning algorithm; motor speed; neutral point voltage balance strategy; power supply; speed estimator; speed-sensorless vector control drive system; torque fluctuation; Artificial neural networks; Fluctuations; Induction motors; Inverters; Machine vector control; Power supplies; Power system harmonics; Space vector pulse width modulation; Torque; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Machines and Systems, 2008. ICEMS 2008. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-3826-6
Electronic_ISBN :
978-7-5062-9221-4
Type :
conf
Filename :
4770980
Link To Document :
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