Title :
Fuzzy vector control of induction motor
Author :
Rafa, S. ; Larabi, A. ; Barazane, L. ; Manceur, Malik ; Essounbouli, N. ; Hamzaoui, A.
Author_Institution :
Lab. of the Ind. Electr. Syst., Univ. of Sci. & Technol. Houari, Algiers, Algeria
Abstract :
The aim of this paper consists of presenting a new approach to control an induction motor using type-1 fuzzy logic. The induction motor has a nonlinear model, uncertain and strongly coupled. The vector control technique, which is based on the inverse model of the induction motors, solves the coupling problem. Unfortunately, in practice this is not checked because of uncertainties in the model. Indeed, the presence of uncertainties led us to use the techniques of fuzzy logic. This technique is used to replace the block of field orientated control with a new block control its role is to maintain the decoupling and overcome the problem of robustness with respect to the parametric variations. The simulation results show that the two control schemes provide in their basic configuration, comparable performances regarding the decoupling. However, the choice for the Fuzzy vector control appears advantageous from the point of view robustness.
Keywords :
fuzzy control; induction motors; machine vector control; nonlinear control systems; uncertain systems; coupling problem; fuzzy vector control; induction motor control; induction motor inverse model; nonlinear model; parametric variations; robustness problem; strongly coupled model; type-1 fuzzy logic; uncertain model; vector control technique; Induction motors; MATLAB; Rails; Vectors; Fuzzy vector control; Induction Motor; Vector control; fuzzy modeling;
Conference_Titel :
Networking, Sensing and Control (ICNSC), 2013 10th IEEE International Conference on
Conference_Location :
Evry
Print_ISBN :
978-1-4673-5198-0
Electronic_ISBN :
978-1-4673-5199-7
DOI :
10.1109/ICNSC.2013.6548843