Title :
The research for speed estimation of induction motor based on neural network
Author :
Shao, Zongkai ; Li, Ying
Author_Institution :
Coll. of Inf., Kunming Univ. of Sci. & Technol., China
Abstract :
Artificial neural networks have the ability of parallel calculation, adapting, learning and approaching an arbitrary nonlinear function. In this paper, a method of how to use a single nerve cell to identify motor speed and how to use a multi-input neural network to identify motor stator and rotor resistance online is discussed. The simulation results show its validity and feasibility
Keywords :
control system analysis; induction motors; machine control; machine theory; neurocontrollers; parameter estimation; rotors; stators; velocity control; artificial neural network; control simulation; induction motor; motor speed estimation; multi-input neural network; nerve cell; parallel calculation; rotor resistance estimation; speed estimation; stator resistance estimation; Artificial neural networks; Educational institutions; Equations; Function approximation; Induction motors; Machine vector control; Neural networks; Programmable control; Rotors; Stators;
Conference_Titel :
Power Electronics and Motion Control Conference, 2000. Proceedings. IPEMC 2000. The Third International
Conference_Location :
Beijing
Print_ISBN :
7-80003-464-X
DOI :
10.1109/IPEMC.2000.883009
