Title :
Vector Control of Induction Motors Using Radial Basis Function Neural Network
Author :
Jokar, M.H. ; Abdi, B. ; Ardebili, M.
Author_Institution :
Kliaje Nasir Toosi Univ., Tehran
Abstract :
Due to nonlinear and complex operation, especially in transient statics, induction motors needs special control strategies. In this work, decoupling of speed and rotor flux equations and their simultaneous control are used to achieve the highest efficiency and fast dynamic performance. The highest efficiency is reached when the proper flux is selected and as a result of dynamic decoupling of speed and rotor flux equations, the rotor flux can be modified to achieve the highest efficiency and make the speed be at its desired value. The precise control of these changes has been done using RBF neural network.
Keywords :
induction motors; machine vector control; radial basis function networks; dynamic decoupling; induction motors; radial basis function neural network; rotor flux equations; vector control; Equations; Induction motors; Machine vector control; Magnetic flux; Neural networks; Radial basis function networks; Rotors; Stators; Torque control; Velocity measurement; induction motors; neural networks; vector control;
Conference_Titel :
Diagnostics for Electric Machines, Power Electronics and Drives, 2007. SDEMPED 2007. IEEE International Symposium on
Conference_Location :
Cracow
Print_ISBN :
978-1-4244-1061-3
Electronic_ISBN :
978-1-4244-1062-0
DOI :
10.1109/DEMPED.2007.4393097
