Observation et commande non-linéaire de la machine asynchrone avec identification on line des paramètres.

Abstract

The objective of this thesis is the theoretical study and the practical implementation of the direct torque control of the DTC of a squirrel cage induction motor using non-linear and robust techniques with and without a speed sensor. A practical implementation of the DTC have been realized, then, one aimed at improving the robustness and the stability of the control algorithm by replacing the linear PI Controller used in the speed loop by a nonlinear control law using fuzzy logic control FLC and sliding mode control SMC with exponential reaching law ERL. Using these non-linear techniques with DTC allows for a fast dynamic response, with low ripple rank and robust control against external disturbances and system uncertainties. After that, we inserted a control strategy without speed sensor. The adaptive MRAS reference system was used for the joint on-line estimation of rotational speed, stator resistance, and rotor time constant. Since this technique contains three conventional PI controllers, we will proceed to improve it by combining it with one of the intelligent technologies, namely artificial neural networks.