Tarek Ameid

This paper presents the experimental validation of a Fault-Tolerant Control (FTC) system for Permanent Magnet Synchronous Motor (PMSM) drives, specifically focusing on current sensors. The FTC system is designed to detect and diagnose both single and multiple faults in the current sensors and to reconfigure the control loop to ensure uninterrupted operation in the presence of such faults. Several crucial aspects are addressed in the proposed approach, including fault detection, isolation of faulty sensors, and reconfiguration of the control system through accurate current estimation. To achieve this, a novel adaptation of the Luenberger observer is proposed and employed for estimating the stator currents. The effectiveness of the fault-tolerant control strategy is demonstrated through experimental tests conducted on a 7.2 kW PMSM utilizing a field-oriented vectorial strategy implemented in a dSpace 1104 platform.

This paper introduces a simple and low-cost direct vector control method without current sensors for Permanent Magnet Synchronous Motor (PMSM) drives, using only a single estimator and the measured dc-link voltage, as well as the measured rotor speed for currents reconstruction. The proposed method is based on a new modification of the adaptive state observer to estimate the line currents. A theoretical concept is developed, the modified adaptive state observer is presented. Simulations tests are performed to prove the ability of the proposed scheme to reconstruct stator currents and reproduce the performances of a basic and traditional vector control PMSM drive.

Finite-State Model Predictive Control methods (FSMPC) have been presented recently in the field of electrical drive and power electronics as an alternative to the conventional strategies. This paper presents a comparative evaluation between Direct Torque Control (DTC) and two finite-state model predictive control strategies applied to induction motor drive. Both DTC and MPC are nonlinear control techniques which dispense with the use of modulation unit (i.e. pulse width modulator (PWM) or space vector modulator (SVM)). DTC can provide good decoupled flux and torque control using pair of hysteresis comparators and lookup switching table for voltage vectors selection. In contrast with the model predictive control which includes the inverter model in control design. The optimal selection of inverter switching states minimizes the error between references and the predicted values of control variables by the optimization of a cost function. The effectiveness of applied algorithms is investigated by an experimental implementation using real-time interface (RTI) based on dSpace 1104.

This paper presents a rotor bars fault diagnosis in low-speed for the induction motor drive. The backstepping algorithm is employed to preserve a good control performance and to avoid different uncertainties in order to have good signals acquisition for the diagnosis process. The used technique for the fault detection is the discrete wavelet transforms which applied to analyze the stator phase current and the output signal of the speed regulator. Furthermore, the calculation of the energy stored in each decomposition can evaluate the effect of the fault. The controls of the induction motor and their diagnosis have been investigated experimentally using Matlab/Simulink environment with Real-Time interface based on the dSpace 1104.