Title :
Design and Simulation of Artificial-Neural-Network-Based Rotor Resistance Observer of Induction Motors
Author :
Sheng-Wei, Gao ; You-Hua, Wang ; Yan, Cai ; Chuang, Zhang
Author_Institution :
Province-Minist. Joint Key Lab. of EF & EAR, Hebei Univ. of Technol., Tianjin, China
Abstract :
The performance of the vector control depends on the precise measurements of parameters in motor. The rotor resistance is one of the most important parameters. And its variation is very significant because of the temperature rise and skin effect during the implementation of control. A rotor resistance estimation method based on artificial neural network (ANN) is proposed in this paper combining with the voltage model rotor flux and the current model rotor flux. The method can get the suitable rotor resistance value by the provided observer. Simulation results are given to verify that the proposed algorithm is useful to identify the rotor resistance accurately and rapidly so as to enhance its Robustness.
Keywords :
electric current control; induction motors; machine vector control; neurocontrollers; observers; rotors; voltage control; artificial-neural-network-based rotor resistance observer; current model rotor flux; induction motors; precise measurements; rotor resistance estimation method; skin effect; temperature rise; vector control; voltage model rotor flux; Angular velocity control; Artificial neural networks; Electric resistance; Induction motors; Intelligent networks; Power system modeling; Rotors; Stators; Synchronous motors; Voltage control; neural networks; parameter identification; rotor resistance; vector control;
Conference_Titel :
Intelligent Networks and Intelligent Systems, 2009. ICINIS '09. Second International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-5557-7
Electronic_ISBN :
978-0-7695-3852-5
DOI :
10.1109/ICINIS.2009.156