This article presents the results of experimental work carried out both in situ (coring; pressuremeter test) and in the laboratory (drying-wetting and oedometric tests) to describe the volumetric behavior on drying-wetting path of a swelling clayey soil of eastern Algeria. In order to perform drying-wetting tests the osmotic technique and saturated salts solutions were used. These suction-imposed methods have gained widespread acceptance as reliable methods for imposing suction on soil specimens. They allowed to sweep a wide range of suctions between 0 and 500 MPa. The ability to impose suction on soil specimens allows for drying and wetting stress paths to be applied to evaluate resulting changes in state parameters (void ratio, degree of saturation and water content). These paths were carried out on specimens with different initial states. Slurries of soil were used to characterize the reference behavior, while the undisturbed soil samples allow to describe the behavior of material under in situ conditions. In the last part of this article and to specify the behavior observed in the saturated domain, a comparison between the resulting deformations of the drying-wetting test and those resulting from the oedometric test was made.

This papers deal with a new Adaptive Direct Power Control for Doubly-Fed Induction Generator of 1.5 MW. The main feature of the proposed strategy is based on the replacement of the fixed switching table by an adaptive one. The online update of the adaptive switching table depends on the reactive power variation and past switching sequences. The proposed adaptive direct power control is compared with Vector Control and Classical Direct Power Control. The robustness of the proposed control scheme against parameter, load and wind speed variations have done with success. The main performance of the Adaptive Direct Power Control strategy is the reduction of powers ripples, thus reduce of torque ripple on the shaft of the turbine.

Cette thèse traite la modélisation, le contrôle et la simulation d’un système de conversion d’énergie éolienne à base d’une machine synchrone à aimants permanents (GSAP) connectée au réseau. Il est nécessaire de lier cette génératrice avec la charge ou le réseau par des convertisseurs statiques susceptibles d’améliorer la qualité d’énergie en tension et fréquence en utilisant des techniques adéquates de commande. L’étude consiste à implémenter des stratégies de contrôle pour assurer une meilleure qualité d’énergie. Après la modélisation de la cha{\^ıne de conversion d’énergie éolienne complète avec exploitation de la commande MPPT, une application de la commande directe du couple basée sur des régulateurs à hystérésis et la commande DTC-SVM sont introduites à la machine pour mettre en évidences les performances de ces dernières. D’après les résultats de simulation obtenus, la commande DTC-SVM présente de meilleures performances par rapport à la DTC classique et la commande vectorielle

Cette thèse a pour but d’apporter une contribution au contrôle DTC de la MASDE. Plusieurs structures ont été développées ces structures concernant la combinaison de différentes techniques de commandes intelligentes avec l’apport des techniques d’optimisations. Dans ce contexte une commande floue type 1 et flou type 2 ont été présentée avec l’utilisation des techniques PSO et AG dont le but est d’améliorer les performances de la MASDE, avec ces techniques les oscillations de flux et couple sont réduites, et la réponse dynamique du système a été améliorée. Dans ce travail, nous avons aussi développé une autre technique qui réduit les oscillations de couple et de flux, cette technique que nous avons appelée commande DTC hybride basée sur le mode glissant d’ordre supérieur flou-T2. L’ensemble des résultats obtenus a montré satisfaction quant aux performances atteintes par le système. Celles-ci sont traduites par la robustesse de la commande vis-à-vis des incertitudes paramétriques de la MASDE.

Ce travail est basé sur l’étude et la simulation numérique du comportement de la micropompe piézoélectrique à mouvement péristaltique. La nature de l’actionneur piézoélectrique est un disque piézoélectrique PZT-5H (Titano-Zirconate de Plomb) et le diaphragme est un dioxyde de silicium (SiO2). En appliquant l’approche FSI (Fluid-Structure Interaction), la simulation de la micropompe sans valves est réalisée au moyen du logiciel Comsol 3.5 Multiphysics. La déformation dûe à la tension appliquée aux bornes du disque piézoélectrique entra{\^ıne un déplacement de la membrane, et par la meme la circulation du fluide. A partir des résultats obtenus, la conception optimale a nécessité respectivement une épaisseur de 0.5 mm pour la membrane et pour l’actionneur piézoéléctrique. L’étude des effets de la tension sur la déflexion du diaphragme et la nature du fluide sur le débit de la micropompe a été menée et des résultats de simulation probants ont été obtenus

Ce travail présente des techniques de commande robustes dédiées au système éolien basé sur la machine asynchrone à double alimentation sans balais (MADASB) entrainée par une turbine à calage variable des pales. Le stator de puissance de la machine est directement relié au réseau électrique ; par contre le stator de commande est alimenté par un convertisseur bidirectionnel. Les MADASB promettent des avantages significatifs pour les systèmes de conversion d’énergie éolienne en raison de leurs faibles coûts et une plus grande fiabilité par rapport aux machines asynchrones à double alimentation classiques (MADA). L’idée principale consiste à appliquer différentes techniques de commande pour le contrôle indépendant des puissances active et réactive générées par la MADASB découplée par la technique de commande vectorielle. Il s’agit particulièrement de la commande par logique floue et des commandes par mode glissant d’ordre un et de second ordre basée sur l’algorithme du Super-Twisting, la commande par retour d’état et la commande par backstepping. Une étude comparative relative aux performances obtenues par les commandes proposées est menée. Les résultats de simulation montrent que ces méthodes hiérarchisées, possèdent de grandes performances dans le contrôle de tels systèmes en termes de poursuite de la référence, de découplage, de temps de réponse et de la qualité du courant.

Cette thèse a pour but d’apporter une contribution au contrôle direct des puissances d’une chaine de conversion d’énergie éolienne à base d’une GADA en faisant varier la vitesse de l’éolienne en réponse au changement de la vitesse du vent afin d’optimiser l’énergie éolienne extraite et de concevoir une commande robuste face aux incertitudes paramétriques. Plusieurs structures ont été développées ces structures concernant la combinaison de déférentes techniques de commandes pour aboutir à des meilleurs résultats. Dans ce contexte une commande adaptative pour le contrôle des puissances de la GADA a été présentée, avec cette technique les oscillations des puissances sont réduites, la réponse dynamique du système a été améliorée. Dans ce travail, nous avons aussi développé une autre technique qui réduit les oscillations des puissances, cette technique que nous avons appelé DPC basée sur le mode glissant d’ordre supérieur. L’ensemble des résultats obtenus a montré satisfaction quant aux performances atteintes par le système. Celles-ci sont traduites par la robustesse de la commande vis-à-vis des incertitudes paramétriques de la GADA

In this paper, a high-performance indirect field-oriented controlled dual Induction Motor (IM) drive fed by a single inverter using type-2 fuzzy logic control will be presented. At first, the mathematical model of the IM is implemented in the d-q reference frame. Then, the speed control of the Dual Induction Motor (DIM) operating in parallel configuration with Indirect Field Oriented Control (IFOC) using PI and type-2 Fuzzy Logic Controller (T2-FLC) will be presented. For the control of this system, a DC supply and a Space Vector Pulse Width Modulation (SVPWM) voltage source inverter are introduced with constant switching frequency. Also, the performance of T2-FLC, which is based on the IFOC, is tested and compared to those achieved using the PI controller. The simulation results demonstrate that the T2-FLC is more robust, efficient, and has superior dynamic performance for traction system applications.

In this paper, a direct vector control using fuzzy logic controller with adaptive gain for a doubly fed induction generator (DFIG) based wind energy conversion system (WECS) is presented. The performance of fuzzy controllers is characterized by unsatisfactory performance: (wide overshoot, excessive oscillations and sensitivity to parametric variations). We propose a robust method, where the control gain will be continually adapted with the use of a set of fuzzy rules; we only consider the gain adaptation of the command. I mean the value of the gain will be determined by a rule base defined by the error and the variation of the error. Finally, the control of the active and reactive powers using a fuzzy logic controller with adaptive gain is simulated using software Matlab/Simulink, studies on a 1.5 MW DFIG wind generation system compared with the conventional fuzzy logic controller. Performance and robustness results obtained are presented and analyzed. KEY WORDS Wind energy conversion system ; Vector control ; Fuzzy logic controller ; Adaptive fuzzy logic controller.

This paper presents a hybrid scheme for the control of active and reactive powers using the direct vector control with stator flux orientation (SFO) of the DFIG. The hybrid scheme consists of Fuzzy logic, Reference Signal Tracking (F-RST) controllers. The proposed (F-RST) controller is compared with the classical Proportional-Integral (PI) and the Polynomial (RST) based on the pole placement theory. The various strategies are analyzed and compared in terms of tracking, robustness, and sensitivity to the speed variation. Simulations are done using MATLAB software. The simulation results prove that the proposed approach leads to good performances such as the tracking test, the rejection of disturbances and the robustness concerning the parameter variations. The hybrid controller is much more efficient compared to those of PI and RST controller, it also improves the performance of the powers and ensures some important strength despite the parameter variation of the DFIG.

This paper presents a novel direct rotor flux oriented control with online estimation of magnetizing current and magnetizing inductance applied to self-excited dual star induction generator equipping a wind turbine in remote sites. The induction generator is connected to nonlinear load through two PWM rectifiers. The fuzzy logic controller is used to ensure the DC bus voltage a constant value when changes in speed and load conditions. In this study, a performance comparison between the conventional approach and the novel approach is made. The proposed control strategy is validated by simulation in Matlab/Simulink.

Les énergies renouvelables prennent ces dernières années un axe d’investigation pour les chercheurs. Pour cette raison, notre étude est consacrée à l’application des différentes commandes non linéaires à la génératrice asynchrone double alimentée (GADA) intégrée dans un système de conversion de l’énergie éolienne. En premier lieu on présente l’application de la commande vectorielle associée à un système éolien. Pour raison d’amélioration des performances, des commandes avancées de type Mode Glissant (MG) et Backstepping (Back) sont appliquées à la GADA-éolienne afin d’assurer un découplage entre les puissances active et réactive pour des vitesses fixe et variable avec des performances souhaitées. La stratégie MPPT (Maximum Power Point Track) pour extraire le maximum de puissance pendant la conversion est développée. Aussi, la technique SVM (Space Vector Modulation) est appliquée. L’étude comparative des différentes commandes étudiées à travers les résultats des simulations montre une amélioration significative des performances des contrôleurs non linéaires, Backstepping (Back) et Mode Glissant (MG) proposés par rapport au contrôleur vectoriel en termes de réponse dynamique, de rejet des perturbations et des variations paramétriques

The combination of neural networks and fuzzy controllers is considered as the most efficient approach for different functions approximation, and indicates their ability to control nonlinear dynamical systems. This paper presents a hybrid control strategy called Neuro-Fuzzy Sliding Mode Control (NFSMC) based on the Brushless Doubly fed Induction Generator (BDFIG). This replaces the sliding surface of the control to exclude chattering phenomenon caused by the discontinuous control action. This technique offers attractive features, such as robustness to parameter variations. Simulations results of 2.5 KW BDFIG have been presented to validate the effectiveness and robustness of the proposed approach in the presence of uncertainties with respect to vector control (VC) and sliding mode control (SMC). We compare the static and dynamic characteristics of the three control techniques under the same operating conditions and in the same simulation configuration. The proposed controller schemes (NFSMC) are effective in reducing the ripple of active and reactive powers, effectively suppress sliding-mode chattering and the effects of parametric uncertainties not affecting system performance.

The increasing complexity of most industrial processes always tends to create problems in monitoring and supervision systems. Detection and early fault diagnosis are the best way to manage and solve these problems. Artificial neural networks (ANNs), by their ability to learn and store a large volume of information, are tools particularly suitable for diagnostic support systems. Effectiveness of ANNs for fault diagnosis in milk pasteurization process is presented in this paper. The initial data base used for fault diagnosis is constructed using data extracted from FMEA (Failure Modes and Effects Analysis) tables of milk pasteurization process. Indeed, this analysis makes it possible to establish the links of cause and effect between the faulty components and the observed symptoms. Three models of ANNs, namely Feed-Forward Back Propagation (FFBP), Radial Basis Function based Neural Network (RBNN), and Generalized Regression Neural Networks (GRNN) are developed and compared. The determination coefficient (R2 ), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) statistics were used as evaluation criteria of all the models. The comparison results indicate that the performances of GRNN model are better than the FFBP and RBNN models. The same neuronal models can be extended to any technical system by considering appropriate parameters and defects.

Research on risk matrices show that there is considerable diversity in the practice of designing risk matrices. This has led to serious problems of standardization and communication. Indeed, these problems affect at the same time on the development of matrices and in their exploitation in term of risk assessment. To solve these problems, this paper proposes an experience feedback method that aims to capitalize the feedback invariants resulting from the analysis of existing risk matrices. This capitalization allows developing a theoretical framework of the robust risk matrices design. The application of the proposed method for examples of matrices confirms the interest of articulating these risk matrices designs through an argument based on experience feedback. In this sense, the merit of the proposed experience feedback method is that it promotes the sharing of knowledge between the actors involved in a risk assessment.

The ageing of the Algerian oil and gas (O&G) installations has led to many incidents. Such installations are over 30 years old (life cycle) and still in operation. To deal with this O&G crucial problem, the Algerian authorities have launched a rehabilitation and modernization schedule of these installations. Within the framework of this program, many audit operations are initiated to elaborate a general diagnosis of the works to be performed while optimizing production. In other words, industrial ageing risks shall be controlled. In the process safety management (PSM) context, the aim of this paper is to study ageing problem of the Algerian industrial installations through proposed indicators. Their prioritization adjusted by (TOPSIS) Technique for Order-Preference by Similarity to Ideal Solution method which allows identification of ageing control solutions of Algerian onshore fields.

Purpose The purpose of this paper is to develop an advanced decision-making support for the appropriate responding to critical alarms in the hazardous industrial facilities. Design/methodology/approach A fuzzy analytical hierarchy process is suggested by considering three alternatives and four criteria using triangular fuzzy numbers to handle the associated uncertainty. A logarithmic fuzzy preference programming (LFPP)-based nonlinear priority method is employed to analyze the suggested model. Findings A quantitative decision-making support is not only a necessity in responding to critical alarms but also easy to implement even in a relatively short reaction time. Confirmation may not be the appropriate option to deal with a critical alarm, even with the availability of the needed resources. Practical implications A situation related to a flammable gas alarm in a gas plant is treated using the developed model showing its practical efficiency and practicality. Originality/value The proposed model provides a rational, simple and holistic fuzzy multi criteria tool with a refined number of criteria and alternatives using an LFPP method to handle process alarms.

Purpose The purpose of this paper is to achieve the national strategic agenda’s criteria that aim for accomplishing sustainable buildings by estimating the effects of energy efficiency measures in order to reduce energy consumption and CO2 emission. Design/methodology/approach A design approach has been developed based on simulation software and a modeled building. Therefore, a typical office building is considered for testing five efficiency measures in three climatic conditions in Algeria. This approach is conducted in two phases: first, the analysis of each measure’s effect is independently carried out in terms of cooling energy and heating energy intensities. Then, a combination of optimal measures for each climate zone is measured in terms of three sustainable indicators: final energy consumption, energy cost saving and CO2 emission. Findings The results reveal that a combination of optimal measures has a substantial impact on building energy saving and CO2 emission. This saving can rise to 41 and 31 percent in a hot and cold climate, respectively. Furthermore, it is concluded that obtaining higher building performance, different design alternatives should be adapted to the climate proprieties and the local construction materials must be applied. Originality/value This study is considered as an opportunity for achieving the national strategy, as it may contribute in improving office building performance and demonstrating a suitable tool to assist stakeholders in the decision making of most important parameters in the design stage for new or retrofit buildings.

Aiming to provide a generalized method for assessing the performance of safety instrumented systems with a flexible and accurate consideration of the common cause failures’ contribution. This paper is devoted to the development of a direct way to generate the transition rate matrix associated with the continuous-time Markov model of any typical KooN architecture using any parametric model. Such a choice is considered after a detailed comparison of the ability of several dependability methods (e.g., fault trees, reliability block diagrams, Markov models, Bayesian networks, etc) to provide simple representations and genuine results in this context. To validate the developed method, the unavailability and the unconditional failure intensity of a wide range of configurations are quantified using the Binomial Failure Rate model and compared to those of the complete fault tree implementation.

Purpose The purpose of this paper is to show the impact of operational and environmental conditions (risk influencing factors) on the component criticality of safety barriers, safety barrier performance and accidents frequency and therefore on risk levels. Design/methodology/approach The methodology focuses on the integration of criticality importance analysis in barrier and operational risk analysis method, abbreviated as BORA-CIA. First, the impact of risk influencing factors (RIFs) associated with basic events on safety barrier performance and accident frequency is studied, and then, a risk evaluation is performed. Finally, how unacceptable risks can be mitigated regarding risk criteria is analyzed. Findings In the proposed approach (BORA-CIA), the authors show how specific installation conditions influence risk levels and analyze the prioritization of components to improve safety barrier performance in oil and gas process. Practical implications The proposed methodology seems to be a powerful tool in risk decision. Ordering components of safety barriers taking into account RIFs allow maintenance strategies to be undertaken according to the real environment far from average data. Also, maintenance costs would be estimated adequately. Originality/value In this paper, an improved BORA method is developed by incorporating CIA. More precisely, the variability of criticality importance factors of components is used to analyze the prioritization of maintenance actions in an operational environment.