Title :
Neural network speed identification scheme for speed sensor-less DTC induction motor drive system
Author :
Ma, Xianmin ; Na, Zhi
Author_Institution :
Dept. of Autom. Eng., Xi´´an Univ. of Sci. & Technol., China
Abstract :
A novel neural network speed identification scheme for the speed sensorless direct torque control (DTC) of an induction motor drive system is presented in the paper. The system uses current and voltage sensors for rotor speed and rotor flux estimation with a digital signal processor (DSP) TMS320F240 in a closed loop control system. Rotor speed identification is based on the model reference adaptive control (MRAC) theory with a neural network using the backpropagation (BP) algorithm. The suggested speed identification method has been validated by a simulation study
Keywords :
backpropagation; control system analysis; control system synthesis; induction motor drives; machine theory; machine vector control; model reference adaptive control systems; neurocontrollers; parameter estimation; torque control; velocity control; backpropagation algorithm; closed loop control system; control design; control simulation; current sensors; induction motor drive; model reference adaptive control; neural network speed identification scheme; rotor flux estimation; rotor speed estimation; speed sensorless direct torque control; voltage sensors; Control systems; Digital signal processing; Digital signal processors; Induction motor drives; Neural networks; Rotors; Sensor systems; Sensorless control; Torque control; Voltage control;
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.2000.883013
