Contrôle par mode glissant: Observation et estimation paramétrique d’une machine à induction avec défauts

Le travail présenté dans cette thèse est consacré à l’étude de la commande par mode glissant d’une machine asynchrone en présence des défauts. Les défauts de la machine pris en compte dans ce travail sont: les cassures de barres, court-circuit entre les spires dans l’enroulement statorique et l’excentricité mixte du rotor. Deux principales méthodes sont utilisées pour la détection des défauts de la machine asynchrone, méthodes de diagnostic sans connaissance et avec connaissance a priori. L’une est basée sur l’extraction d’informations par les biais du traitement des signaux mesurés qui sont (courants, vitesse etc …). La seconde méthode est basée sur le suivi des paramètres et des grandeurs de la machine, au moyen d’algorithmes d’observations (filtre de Kalman étendu, adaptatif et par mode glissant). La loi de commande classique PI peut être insuffisante puisqu’elle est moins robuste notamment lorsque les exigences sur la précision et autres caractéristiques dynamiques du système sont strictes. La commande par mode glissant montre que les performances sont meilleures autour du point de fonctionnement, aussi bien par rapport à des variations paramétriques et des perturbations extérieures. Pour atténuer ou éliminer le phénomène du chattering, des solutions ont été proposées en remplaçant le terme discontinu (fonction signe) par une fonction continue (saturation, intégrale etc …). L’utilisation de cette dernière produit une erreur statique en présence de perturbations, l’algorithme twisting du mode glissant d’ordre deux pour assurer la convergence de la surface vers l’origine en un temps fini. Toutes les commandes et les approches proposées sont illustrées et validées par simulations

Discrete wavelet transform and energy eigen value for rotor bars fault detection in variable speed field-oriented control of induction motor drive

International audienceThis paper presents a methodology for the broken rotor bars fault detection is considered when the rotor speed varies continuously and the induction machine is controlled by Field-Oriented Control (FOC). The rotor fault detection is obtained by analyzing a several mechanical and electrical quantities (i.e., rotor speed, stator phase current and output signal of the speed regulator) by the Discrete Wavelet Transform (DWT) in variable speed drives. The severity of the fault is obtained by stored energy calculation for active power signal. Hence, it can be a useful solution as fault indicator. The FOC is implemented in order to preserve a good performance speed control; to compensate the broken rotor bars effect in the mechanical speed and to ensure the operation continuity and to investigate the fault effect in the variable speed. The effectiveness of the technique is evaluated in simulation and in a real-time implementation by using Matlab/Simulink with the real-time interface (RTI) based on dSpace 1104 board

An Improved Direct Torque Control with an Advanced Broken-Bar Fault Diagnosis for Induction Motor Drives

This paper presents an advanced strategy combining fuzzy logic and artificial neural networks (ANNs) for direct torque control (DTC) and broken-bar fault diagnosis in induction motors. More specifically, a fuzzy-based controller is used to simultaneously minimize the stator flux and the electromagnetic torque ripples. A neural switching table is then proposed to achieve the interface inverter control. Besides, a closed-loop broken-bar fault detection strategy based on the Hilbert technique (HT) with the discrete wavelet transform (DWT) and ANNs is proposed. The fault detection is performed by analyzing the induction motor’s stator current by using the combined techniques HT-DWT. The effect of a broken-bar fault on the machine varies according to the number and position of the broken bars. The neural detector was used in order to identify the number of broken bars through only one current measurement. The effectiveness of the developed control has been verified using MATLAB/Simulink and real-time simulation in OPAL-RT 4510. Obtained results show improved performances in terms of torque ripple minimization and stator current quality, evaluated, respectively, at 43.75% and 41.26% as well as a rigorous motor health monitoring

An automatic rotor bar fault diagnosis using fuzzy logic and DWT-energy for backstepping control driven induction motor in low-speed operation

The contribution of rotor bar fault diagnosis and classification in low-speed induction motor drives under varying load torques has been a topic of limited discussion in the literature. Within this respect, the present paper will be discussing this condition. To ensure control performance and investigate the diagnosis process in low-speed operations, the backstepping algorithm is utilized to handle uncertainties. The discrete wavelet transform is employed to detect faults and decompose signals at various levels, while the fuzzy logic algorithm is applied to classify the fault severity. This study's novelty lies in evaluating fault severity for no/low-load conditions by using the energy approximation obtained from the discrete wavelet transforms of the speed regulator's output signal. This approximation is then used as input for the fuzzy fault classification algorithm. The control algorithm and fault diagnosis are validated experimentally using MATLAB/Simulink with a real-time interface based on dSpace 1104 implementation. The results obtained from this procedure demonstrate successful fault detection and severity classification using both the discrete wavelet approximation and its energy eigenvalue

Rotor fault detection using hybrid signal processing approach for sensorless Backstepping control driven induction motor at low‐speed operation

The present paper proposes a detection method of the broken rotor bar fault in an induction motor at low-speed operation. The diagnosis method is based at the first place, on Hilbert Transform (HT) that is used to extract the stator current envelope; then on Discrete Wavelet Transform (DWT) which processes the previously produced signal. As such, the calculation of the stored energy on envelope levels allows to determine the severity of the fault. In this work, the induction motor is controlled at the very low-speed range and rated load via using sensorless Backstepping control. This nonlinear control is executed to preserve a satisfactory performance speed control during the presence of broken rotor bars to ensure operational continuity. Moreover, Model Reference Adaptive System (MRAS) is used for speed reconstruction to improve the control's system reliability and to reduce its cost. Considerably, through the use of simulation and real-time implementation using MATLAB/Simulink with the dSpace 1104 control board, the effectiveness of the diagnosis and control techniques is evaluated

Sensorless speed estimation and backstepping control of induction motor drive using model reference adaptive system

This paper presents a sensorless nonlinear control for an induction motor drive. The strategy is based on backstepping control in order to ensure a high-performance control and a good dynamic in different uncertainties and external disturbance. Moreover, a model reference adaptive system (MRAS) is used for rotor speed and rotor flux estimations; investigate a sensorless control algorithm by decreasing the cost of the speed sensor. The performances of the sensorless control strategy will be examined via numerical simulation and validated through Hardware implementation using Matlab/Simulink with dSpace 1104 signal card. The results analysis shows the robustness of the sensorless control algorithm for the load disturbances, the speed variation and low-speed

Experimental Implementation of Sensorless Vector Control for IM Drive Using EKF Observer and Fuzzy Logic Controller

This paper presents an implementation of an intelligent control of induction motor (IM) drive. The strategy is based on field-oriented control (FOC) and fuzzy logic approach. The fuzzy logic controller (FLC) will be proposed for rotor speed, direct and quadratic current regulation to cover the drawbacks of the conventional PI controller and to ensure an accurate reference tracking; a robust response against different uncertainties. An Extended Kalman Filter (EKF) is used for rotor speed and flux estimation. This observer can improve the performance of the controlled system by increasing its reliability and decreasing the cost of the speed sensor. The Proposed sensorless strategy will be examined through Hardware implementation with dSpace 1104 board. The experimental results are presented as a comparative study of the control scheme using PI and fuzzy controllers

Hardware Implementation of Modified Backstepping Control for Sensorless Induction Motor Drive

International audienceThis paper presents a hardware implementation of sensorless Backstepping control for induction motor drive. The presented Backstepping control scheme has been designed in the stationary reference frame to reduce the control algorithm complexity. Furthermore, a full order Luenberger observer has been proposed for speed and torque estimation. Several operation conditions of the IM have been conducted such as load application, speed direction reversal and low-speed condition. In addition, an industrial benchmark test which comprises all speed condition has been done to check the control ability in different operation points. This work presents for the first time the experimental implementation of this developed control algorithm. The obtained experimental results prove the effectiveness and performance of the proposed control scheme

Discrete wavelet transform and energy eigen value for rotor bars fault detection in variable speed field-oriented control of induction motor drive

International audienceThis paper presents a methodology for the broken rotor bars fault detection is considered when the rotor speed varies continuously and the induction machine is controlled by Field-Oriented Control (FOC). The rotor fault detection is obtained by analyzing a several mechanical and electrical quantities (i.e., rotor speed, stator phase current and output signal of the speed regulator) by the Discrete Wavelet Transform (DWT) in variable speed drives. The severity of the fault is obtained by stored energy calculation for active power signal. Hence, it can be a useful solution as fault indicator. The FOC is implemented in order to preserve a good performance speed control; to compensate the broken rotor bars effect in the mechanical speed and to ensure the operation continuity and to investigate the fault effect in the variable speed. The effectiveness of the technique is evaluated in simulation and in a real-time implementation by using Matlab/Simulink with the real-time interface (RTI) based on dSpace 1104 board