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By using the direct torque control (DTC), robust response in ac drives can be produced. Ripples of currents, torque and flux are oberved in steady state. space vector modulation (SVM) applied in DTC and used for a sensorless induction motor (IM) with fuzzy sliding mode speed controller (FSMSC) is studied in this paper. This control can minimize the torque, flux, current and speed pulsations in steady state. To estimate the rotor speed and stator flux the model reference adaptive system (MRAS) is used that is designed from identified voltages and currents. The FSMSC is used to enhance the efficiency and the robustness of the presented system. The DTC transient advantage are maintained, while better quality steady-state performance is produced in sensorless implementation for a wide speed range. The drive system performances have been checked by using Matlab Simultaion, and successful results have been obtained. It is deduced that the proposed control system produces better results than the classical DTC.

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In this paper, we present the linearizing control technique controlled by a neuro-fuzzy regulator applied to the permanent magnet synchronous machine (PMSM). It permits decoupling and linearizing the system without taking into accounts the flux orientation. The nonlinear control (NLC) applied to the PMSM decompose the system into two mono variable, linear and independent subsystems. The neuro-fuzzy control permits to the speed and the I d current control is carried out by neuro-fuzzy regulators (ANFIS). The analysis of the results obtained by this type of nonlinear regulator shows the robustness characteristic with respect to the load perturbations and the parametric variations. A qualitative analysis of the evolution of the principal variables describing the behaviour of the global system (PMSM-Inverter (PWM)-Control) is developed by several tests of digital simulation in last stage. Keywords: PMSM, nonlinear control, Neuro-fuzzy control, three levels inverter I. INTRODUCTIONThe vector control technique permits to compare the PMSM to the separate excitation D.C machine. The vector flux must be concentrated on the D axis with I d current null. However the exact knowledge of the rotoric flux position poses a precision problem [1]. The nonlinear control technique which makes abstraction with the flux orientation permits to solve this problem. It also allows, by a nonlinear state negative feedback, to completely decouple the system in two linear and mono variable subsystems [2,3]. Thus, it is possible to control independently the speed and the forward current I d . The traditional control algorithms (PI or PID) prove to be insufficient where the requirements in performances are very severe. Several methods of control are proposed in the technical literature, among them, the Neuro-fuzzy control which held our attention by the simplicity of its adjustment algorithm and which is the objective of our work. The work is composed by a PMSM modelisation in the Park frame and an overview of the nonlinear control technique in order to decouple the machine model. Then, a brief outline on the Neuro-fuzzy control and its application to the speed and the I d current control of the PMSM supplied with the three levels inverter. In the last step, a comment on the results obtained in simulation and a conclusion where we emphasize the interest and the contribution of this method of control.