M. HERIZI Abdelghafour

Ce cours permet de maîtriser les techniques modernes de l’automatique pour l’identification et l’estimation des modèles des systèmes, sur les plans des principes théoriques et de la mise en œuvre pratique à l’aide de nombreux exemples.

This research primarily focuses on the modeling and simulation of high frequency electromagnetic induction welding of pipes. The objective is to assemble two tubes of varying diameters. We have elucidated the electromagnetic and thermal mathematical models of our welding configuration and conducted a comprehensive analysis of the impact of various parameters on the quality of the welding process.

The primary aim of a vehicle's suspension system is to isolate the vehicle's main body from road irregularities, thus improving passenger comfort and ensuring optimal handling stability. This research discusses a stabilizing fuzzy control design for active vehicle suspension systems. The nonlinear model of the active suspension is then represented using a Takagi-Sugeno (TS) fuzzy model. The control approach uses a TS fuzzy controller utilizing an observer to estimate the state while reducing road disturbances. The closed-loop stability requirements of the vehicle utilizing the fuzzy controller and observer are expressed as a Linear Matrix Inequalities (LMI) problem, which can be effectively resolved through convex optimization methods. In this paper, we study the stability of the nonlinear automotive active suspension system with two degrees of freedom represented by a TS fuzzy model, where we will present the stabilization conditions by state feedback via the PDC (Parallel Distributed Compensation) control law and in the last section we introduced the TS fuzzy observer for the case of non-measurable premise variables.

In the context of the electric vehicle, many research works have been and are still conducted on the different parts of the traction chain. Since the significant appearance of the electric vehicle, the direct current machine is the most used.
In this article, we studied a propulsion system based on an electric vehicle driven by a direct current drive system. The objective of this work is to model the electrical and mechanical part of the traction system of an electric vehicle in general. The modeling generally used is based on a simplified description of the forces created at the interface of the tire and the road as well as on the mechanical description of the overall behavior of the vehicle.

This paper focuses on developing two innovative induction motor (IM) control techniques. These techniques are based on the hybridization of Lyapunov theory (sliding mode) and artificial intelligence (type 1 and type 2 fuzzy logic). We will then compare these two control techniques to determine which is more robust. This comparative analysis will be based on a series of tests that we have carried out, covering the system's transient and steady-state operations under identical conditions. The first test involves observing the simulation results obtained by applying these control techniques to the motor to control the generated mechanical power. This qualitative comparison enables these controls to be evaluated for and without the application of external variations. The second test quantifies the different control laws based on quantified measurements, highlighting the performance of each technique in terms of error and time. This test is called a quantitative comparison. Finally, the last examination involves altering the machine parameters, as these values naturally experience fluctuations caused by diverse physical phenomena like inductance saturation and heating of the resistors. This comparison enables the robustness of the control techniques to be assessed.

This paper proposes a strategy for robust control of the wind turbine using a double-fed induction machine (DFIM) controlled by the park transformation, which allows control commands to be applied to the generated power. By orienting the stator flux, the active and reactive powers generated by the DFIM can be decoupled. The proposed control utilises a combination of sliding mode control and fuzzy logic with 12 linguistic variables. This approach effectively addresses modelling uncertainties in both the generator and wind turbine, resulting in improved performance and production quality in this domain. Simulation results will demonstrate the advantages of this approach over the classic setting.

In this article we present a comparative study between the two nonlinear controls, sliding mode control and backstepping control applied to the doubly fed asynchronous generator (DFIG). To evaluate the performance of the power control equipped with sliding mode control. We carried out a series of simulations in a MATLAB/Simulink environment. For the tracking test, the controlled quantities follow their reference trajectory, without exceeding the active and reactive powers and without static error in steady state. For the regulation test, we observe very good sensitivity to external disturbances due to sudden speed variations, the active and reactive powers are not affected. To evaluate the performance of direct power control, use the backstepping method. We carried out a series of simulations under the same MATLAB/Simulink environment. For the tracking test, the controlled quantities follow their reference trajectory, without exceeding the active and reactive powers and without static error in steady state. For the regulation test, we observe a low sensitivity to external disturbances due to sudden variations in the speed of the wind turbine, the active and reactive powers are affected with a low static error.

One of the most exciting potential uses of photovoltaic (PV) technology is powering water pumps. An improved power extraction method for a solar pumping system that does not need batteries is the goal of this effort. The maximum power point tracking (MPPT) is achieved with the help of the DCDC converter. The BLDC motor also helps the pumping system be more reliable and makes the most of the electricity that the PV array delivers. In addition, to enhance control performance in partial shading situations, an MPPT method has been devised based on the Grey Wolf optimization technique. We have simulated the suggested system using MATLAB and Simulink tools to analyze its efficacy.

Eco-friendly energy transportation has been significantly enhanced by the emergence of Green H2 (GH). Integration of these systems with a variety of renewable energy sources has been made highly feasible by the use of H2 as the primary operational medium in H2-based energy storage systems and fuel cells. An overview of the most recent developments in the synthesis of GH through water electrolyzers that are powered by renewable energy sources is provided in this review. In this paper, a concise summary of numerous production methods and a comprehensive examination of a variety of water electrolyzers are provided. A comprehensive analysis of H2 production methods that employ solar, wind, and hybrid systems is also provided. GH production was subjected to an economic evaluation by contrasting the costs associated with various renewable sources. This study is dedicated to the examination of the advantages and challenges associated with GH and the execution of large-scale commercial operations.

This paper focuses on developing two innovative induction motor (IM) control techniques. These techniques are based on the hybridization of Lyapunov theory (sliding mode) and artificial intelligence (type 1 and type 2 fuzzy logic). We will then compare these two control techniques to determine which is more robust. This comparative analysis will be based on a series of tests that we have carried out, covering the system's transient and steady-state operations under identical conditions. The first test involves observing the simulation results obtained by applying these control techniques to the motor to control the generated mechanical power. This qualitative comparison enables these controls to be evaluated for and without the application of external variations. The second test quantifies the different control laws based on quantified measurements, highlighting the performance of each technique in terms of error and time. This test is called a quantitative comparison. Finally, the last examination involves altering the machine parameters, as these values naturally experience fluctuations caused by diverse physical phenomena like inductance saturation and heating of the resistors. This comparison enables the robustness of the control techniques to be assessed.

This paper presents a novel hybrid type-2 fuzzy sliding mode control approach for regulating active and reactive power exchanged with the utility grid by a doubly-fed induction generator in a wind energy conversion system. The main objective of this hybridization is to eliminate the steady-state chattering phenomenon inherent in sliding mode control while improving the transient delays caused by type-2 fuzzy controllers. In addition, the proposed control approach has proven to be successful in coping with varying generator parameters and exhibited good reference tracking. An in-depth comparative study with state-of-the-art advanced control techniques is also the focus of the present paper. The comparative study has three objectives, namely: a qualitative comparative study that aims to compare response times and reference tracking capabilities; a quantitative evaluation that takes into account time-integrated performance criteria; and finally, robustness capabilities. The simulation results, carried out in the Matlab/Simulink environment, have demonstrated the effectiveness and best performance of the proposed hybrid type-2 fuzzy sliding mode control with respect to other advanced techniques included in the comparison study.

The work in question concerns the study and control of the horizontal axis wind turbine with variable blade pitch. In the initial section, an overview of the state of the art of the turbine was presented, including a description of the most commonly used structures, their respective advantages and disadvantages. Subsequently, a model of the horizontal axis wind turbine, derived from the theoretical study, was constructed. In the third section, the necessary controls to regulate the mechanical power produced by the system were presented and developed. These included an indirect MPPT (Maximum Power Point Tracking) control to maximise the power sensor during low speeds of the wind and a "pitch control" to limit and nominalise the power converted during high wind speeds. Finally, the simulation results obtained enabled the evaluation of the performance of the turbine in question, with the application of the aforementioned controls, in order to ascertain the optimal efficiency and production quality in this area.

This study concerns the electrical drive of a permanent magnet synchronous motor at variable speed. Synchronous motors with permanent magnets are becoming increasingly prevalent in mechanisms due to their superior performance compared to other alternating current motors. Among the numerous control methods developed in the literature, The general objective of our study is to investigate the structure of vector control applied to the PMSM, with a focus on the classic PI (current and speed) regulators. This approach allows for the achievement of notable performance gains, particularly in terms of the system's dynamic response, which is comparable to that of a DC motor.

This work is concerned with the design of an antenna array using SIW technology, where the basic element is a rectangular patch antenna. The main goal is to improve the radiation pattern. This technology allows this type of antenna to be produced at a lower cost and easily integrated into communications systems. The antenna was designed in the HFSS simulator on a FR-4 Epoxy substrate with a dielectric constant of εr=4.4 and a thickness of 1.6mm. Three structures have been proposed: the array antenna (AR2), the array antenna (AR4), and the SIW array antenna (SAR4). This paper proposes to insert metal vias between the four elements of the AR4 antenna to direct the antenna radiation towards the main lobe. The antenna resonates at two different frequencies: 6.1 GHz with a matching coefficient S11=17.77 dB and 6.85 GHz with a matching coefficient S11=16.63dB.

This paper presents a modern approach for the detection and classification of rolling element bearing faults in asynchronous machines using decision tree algorithms. These algorithms offer a robust and interpretable method for fault diagnosis, overcoming the limitations of traditional methods that often require complex signal processing and expert knowledge.
The proposed approach utilizes readily available motor data, such as vibration signals and electrical parameters, as input features for the decision tree model. This eliminates the need for specialized sensors or invasive procedures. The decision tree is trained on a dataset of labeled fault and healthy conditions, enabling it to effectively identify and classify different types of rolling element bearing faults.
The paper demonstrates the effectiveness of the proposed method through experimental validation on real-world data from asynchronous machines. The results show that the decision tree model achieves high accuracy in fault detection and classification, outperforming traditional methods in terms of simplicity, interpretability, and computational efficiency. This work offers a valuable contribution to the field of condition monitoring and fault diagnosis, providing a reliable and practical tool for early detection and classification of rolling element bearing faults in asynchronous machines. This can significantly improve machine reliability, reduce maintenance costs, and prevent catastrophic failures.

The doubly fed induction machine (DFIM) has generated significant attention, particularly as a generator in the field of renewable energies. Indeed, through this presentation, we will explore the reasons for this notable interest by beginning with a description of the machine's structure, detailing its various operating modes and commonly used configurations, while also discussing its advantages and disadvantages. We will then proceed to address the modeling and simulant this machine in the Park reference frame (two-phase reference frame (d,q)) linked to the rotating field, which reduces the complexity of the model, and then presented the simulation results for both the motor and generator functions.

This article examines the vector control of an induction motor (IM) driven by a PWM inverter. Oriented flux vector control is one of the most efficient vector control methods due to its ease of design and implementation. Proportional integral (PI) controllers are used to implement this method. The parameters of these controllers are calculated directly from the machine parameters using traditional analytical methods, which require rigorous calculation and a thorough understanding of all the machine parameters. Our research aims to replace the traditional PI controller with a type 1 fuzzy logic controller, which is tested in an initial speed controller scenario. The simulation of vector control performed by traditional controllers
using Matlab/Simulink and the PI-Fuzzy are contrasted.

Noise is one of the most common occupational hazards, these noise levels represent a potential danger to their hearing and may produce other adverse effects. The role of hearing protection is to reduce the sound level perceived in the ear either with the aim of protecting against the risk of deafness or to improve comfort (sleep, concentration). The main objective is to design a hearing protector equipped with a dominant noise suppression process, making it possible to reduce the loud noises of mining equipment, while allowing voice signals to pass through. This hearing protector contains an electronic circuit designed to be installed in an existing shell so as to be able to carry out performance tests in a noisy environment.

In this work, we are going to develop new control technique based on the orientation of the stator flux with type 2 fuzzy control controllers, to apply to the permanent magnet synchronous motor (PMSM) to solve the parametric variation problems to obtain robust performance in the parametric or external variation point, this motor driven by the stator variables through two converters the main function of these converters in the system under consideration is to connect our permanent magnet synchronous motor to the electrical network in two different ways: one on the network-side converter, which will enable continuous bus control and improve the network-side power factor; the other, on the motor-side converter, which will enable control and optimisation of the energy flow generated by the permanent magnet synchronous motor during periods of motor operation. In the first part we have modelled the motor and its converters. In the second part, we have developed the necessary command to control the mechanical power (speed, torque) produced by this motor in order to ensure optimum yield and production quality. The numerical simulation results obtained during the application of the type 2 fuzzy Logic control on our machine show the effectiveness of this implemented control.

The solid oxide fuel cell (SOFC) is broadly used for distributed and clean power generation. The main problem related to SOFC lies in the difficulties to control the output voltage of the SOFC due to the strong nonlinearity, the rapid changes of the load and the limited fuel flow. The objective of the control of the SOFC system is to maintain the output voltage at a constant level and the fuel utilization rate in a safety interval. In this context, a multiple-input multiple-output (MIMO) discrete-time TakagiSugeno (TS) fuzzy dynamic model with feed forward input is used in this study to describe the dynamic properties of the nonlinear voltage and the fuel utilization rate in a tubular SOFC system. This obtained fuzzy model will be used for the application of constrained fuzzy model predictive control. The simulation results are provided to show the accuracy and the effectiveness of the proposed strategy.

The ear is an organ used by organisms to detect sound in what is called the sense of hearing. The term is used to refer to either the external visible organ of the hearing system or the entire internal hearing system responsible for primary processing of sound. The ear consists of: the outer ear, the middle ear and the inner ear. A person may experience hearing loss due to congenital weakness, senile hearing loss, or exposure to noise...etc. Among the solutions for hearing loss are: earwax removal, surgery and cochlear implants. The most important is hearing aids which are a sound processor that is worn in the ear. The device sends sound signals to a receiver and stimulus implanted under the skin, which stimulates the auditory nerve through electrical pathways installed in the cochlea, and this is the topic we have addressed in our research

In this work, we present the wind regions in Algeria and how to exploit them through the establishment of wind energy plants. First, we talk about the history of this energy in Algeria. Then we talk about the economic advantages of this energy in providing services to isolated rural residents, especially in the southern regions. It also allows sustainable development with limited impact on the environment, which contributes to preserving our fossil resources. Then secondly, we present the areas famous for strong and constant wind speeds throughout the year and production stations. The energy distributed from it, and finally we present the latest numbers and statistics on the production of this energy in Algeria.

This document shows a comparative study between two approaches for the direct torque control of the dual star induction motor drive (DSIM), the first is based on conventional PID, the second uses new heuristic optimization technique based on the grey wolf optimizer GWO-PID. The benefits of this combination can reduce the Dual SIM speed control loop problems. The GWO algorithm has been programmed and implemented in MATLAB. In addition, the most importance appropriate GWO-PID scheme combines simultaneously many index such as reducing high torque ripple, steady-state error is reduced, response time is improved and disturbances do not change the drive performance.

In this work, we will develop a robust control algorithm known for its stability and robustness, this control is based on the theory of lyapunov applied to the induction motor to obtain robust performance in the point of parametric or external variation, this machine driven by stator variables through two bidirectional converters. In the first part we have modelled the machine and its converters. In the second part, we developed the control system needed to control the mechanical power (speed, torque) produced by this machine. The numerical
simulation results obtained by applying this control to our machine show the effectiveness of the control developed.

More recently, an optimization method called PSO "particle swarm optimization", inspired by swarm intelligence, has attracted researchers and been exploited in different fields of technology optimization. This method has become more and more popular. It is characterized by a decentralized way of working that imitates the behavior of swarms of social insects, masses of birds, or schools of fish. As part of this work, we try to apply the PSO algorithm to determine the optimum parameters (𝐾𝑝, 𝐾𝑖 and 𝐾𝑑) of the PID regulator while visualizing our objective function which we seek to minimize the error between the input signal and the output signal. The proposed method was more robust, flexible and effective in terms of dynamic performance like reducing peak overshoot, rise time, response time and static error.

In this work, our objective is to optimize the parameters of a PID regulator, that is to say the coefficients 𝐾𝑝, 𝐾𝑖 and 𝐾𝑑 by the Levenberg-Marquardt (LM) method. Different optimization methods will be presented such as the AG genetic algorithm, ACO ant colony algorithms and particle swarm optimization (PSO). The Levenberg-Marquardt algorithm can be considered as that of Gauss-Newton combined with the confidence region method. This method is robust and efficient in terms of dynamic performance such as reduction of maximum overshoot, rise time, response time and static error. Finally, finishing this work with an application of this technique on a nonlinear system controlled by a PID regulator.

In this work, we are going to develop two control techniques based on the orientation of the stator flux with different controllers, namely: type 1 fuzzy control, type 1 adaptive fuzzy control to apply to the permanent magnet synchronous machine to solve the parametric variation problems to obtain robust performance in the parametric or external variation point, this machine driven by the stator variables through two converters. In the first part we have modelled the machine and its converters. In the second part, we have developed the necessary commands to control the mechanical power (speed, torque) produced by this machine, we have carried out a comparative study between the two control systems developed. The numerical simulation results obtained during the application of the type 1 adaptive fuzzy control on our machine show the effectiveness of this implemented control.

The objective of automatic regulation or control of a process is to keep it as close as possible to its operating optimum. The Ziegler-Nichols method among the methods for optimizing PID regulator gains. This method is based on their experience and some simulations to quickly adjust the parameters of the P, PI and PID regulators. As part of this work, we try to apply the Ziegler-Nichols method to determine the optimum parameters (Kp, Ki, Kd) of the PID regulator while visualizing our objective function which we seek to minimize the error between the signal input and output signal. The studied method was robust, flexible and efficient in terms of dynamic performance such as reduction of peak overshoot, rise time, response time and static error.

This paper presents a reliable control technique for the doubly-fed induction generator used in the wind energy conversion system, where the stator flux direction is used to separate the active and reactive power produced by the DFIG. It is possible to maximise the energy output (efficiency) using the proposed control, which combines sliding mode control with type-2 fuzzy logic. This technique is resistant to the modelling uncertainties of the generator and the wind turbine. Finally, simulation on Matlab/Simulink was used to evaluate and compare the performance of the system in terms of compliance and robustness to DFIG parameter variations.

More recently, an optimisation method called "curve fitting", inspired by error minimisation, has attracted researchers and has been used in various areas of optimisation. This method has become increasingly popular. It is based on the principle of least squares, i.e. minimising the sum of errors. As part of this work, we try to apply the curve fitting algorithm to determine the best curves in general cases (linear and non-linear), while visualising our objective function, which we seek to minimise the error between the experimental signal and the estimated signal. The proposed method was more robust, flexible and efficient in terms of dynamic performance such as reduction in peak overshoot, rise time, response time and static error.

To achieve efficient control of a dynamic system, we must have a mathematical model that satisfactorily represents the real behaviour of the system. In this paper we present the modelling of an inverted pendulum. We develop the mathematical model of an inverted pendulum based on the EulerLagrange formalism, followed by a linearisation around the two possible equilibrium points. A series of simulations carried out using the Matlab/Simulink software have been considered, not only with the aim of validating the model obtained, but also with a view to using them to validate the control strategies developed in future work.

Solid Oxide Fuel Cells (SOFCs) are electrochemical devices operating at high temperatures, directly transforming chemical energy into electrical energy, offering significant potential as a clean and efficient power generation technology. The primary challenge concerning SOFCs is the intricacy of regulating the output voltage. This challenge is attributed to the strong nonlinearity, swift load variations, and restricted fuel flow. The primary objective of the SOFC system's control is to maintain a constant level of the output voltage respecting the safety intervals of the fuel utilization rate and the oxy/Hyd ratio. In this context, a new adaptive fuzzy PID controller (FPID) approach is proposed to control the output voltage of the SOFC nonlinear system, where two FPIDs controllers were used one for the hydrogen flow and the other for the oxygen flow. Simulation results are presented to demonstrate the effectiveness and accuracy of the proposed approach in front of other control strategists that use a constant ratio between the reactants.

In this paper, we will develop an adaptive control algorithm applied to the wind energy conversion system (WECS) based on a double-fed induction machine (DFIM) driven by a turbine with variable blade pitch, and controlled through the rotor variables by two bidirectional converters. The main function of these converters in the considered system is the connection of the wind generator to the power grid in two different ways: one on the grid side converter which will allow continuous bus control and improve the power factor on the grid side; the other, on the converter on the rotor side, which will allow the control and optimization of the energy flow generated by the stator during the periods of operation of this system. In the first part we presented the individual modeling of the wind turbine chain, then we presented and developed the controls necessary to control the active and reactive powers produced by this system in order to ensure optimum performance and production quality.

The objective of automatic regulation or control of a process is to keep it as close as possible to its optimum functioning. Fuzzy logic controllers among the modern methods of optimizing the system response. Fuzzy logic is usually expressed by linguistic rules of the form IF-THEN. Within the framework of this work, we try to replace the controller (PI-classic) by a controller based on the fuzzy logic to improve the response of the system.
The goal of our study is to try to minimize the error between the input signal and the output signal. The studied technique was robust and effective in terms of dynamic performance such as reduction of maximum overshoot, rise time, response time and static error.

The control of the doubly-fed induction motor is a complex operation because of this motor characterised by a non-linear multivariable dynamics, having settings that change over time and a significant link between the mechanical component and magnetic behavior (flux) (speed and couple). This article then proposes a new strategy of a robust control of this motor, which is decoupled due to the stator flux’s direction. The proposed control is integrated with the backstepping control which based on Lyapunov theory; this approach consists in
constructively designing a control law of nonlinear systems by considering some state variables as being virtual commands, and the important branch of artificial intelligence type-2 fuzzy logic. The hybrid control backstepping-fuzzy logic consists in replacing the regulators applied to the backstepping control by regulators based on type-2 fuzzy logic. This control will be evaluated by numerous simulations where there is a parametric and non-parametric variation.

Ce cours a pour objectif de maîtriser les techniques modernes de l’automatique pour l’identification et l’estimation des modèles des systèmes, sur les plans des principes théoriques et de la mise en œuvre pratique à l’aide de nombreux exemples.

This paper presents a design modeling of ‎short circuit faults in the stator ‎windings for a Permanent ‎Magnet ‎Synchronous Machine (PMSM).‎ The studied approach is based on developing two mathematical models describing the studied machine's healthy and faulty states.‎ Furthermore, to study the behavior of the overall system, formed by the considered machine and its drive, a dynamic ‎model of the drive is elaborated to study its comportment in various ‎fault ‎conditions.‎ Based on frequency analysis, the Fast Fourier Transform (FFT) is adopted to detect the occurrence of short-circuited turns to highlight relevant features revealing the stator winding faults.‎ The ‎spectral analysis of the ‎stator current decomposition shows ‎the total harmonic distortion (THD), which can be ‎used as a ‎reliable ‎predictor of (ITSC) faults.‎Simulation results for the "healthy" and "faulty" states of the machine show the application contribution of the FFT ‎for stator fault detection.‎

The main idea of this work is to exploit the "BACKSTEPPING" technique based on Lyapunov’s theory for designing stabilizing controls for a special recursive class of nonlinear systems. By considering some state variables as being virtual controls, and designing intermediate control laws for them. Some internal variables are sometimes inaccessible to measurement or expensive to measure, hence the introduction of observers based on the same principle.
Finally, we applied this technique to DC motor, and according to the results we find, (short response time, good disturbance rejection and good accuracy in steady state), we think this means that the back stepping technique offers the best possible performance, and the simulation results confirm it.

In this paper, the fuzzy adaptive gain monitoring method (AGFLC) uses direct field-oriented control (DFOC) to monitor the speed of permanent magnet synchronous motors (PMSM). This surveillance strategy can detect the error of the velocity parameter, forcing the monitored system to achieve the desired reference model, and eliminating the velocity error. First, we examine the mathematical model describing the internal behavior of PMSM to design our system based on the priory physical model of the system. Then, we propose an intelligent method that combines a fuzzy control algorithm with its related control rules, aiming to monitor the speed of PMSM. This problem is solved by combining the two parameters
of error and its variation. A fuzzy algorithm has proven to be an effective method to adjust the speed by suppressing disturbances. Furthermore, an adapted gain fuzzy controller, which provides a fast dynamic response without overshooting at various dynamic actions, has been suggested to compensate for all external disturbances. The obtained simulation results demonstrate the efficiency of the monitoring method for fault detection and localization and verify the performance of the adaptive algorithm control system.

The main idea of this work is to exploit the "BACKSTEPPING" technique based on Lyapunov’s theory for the control of nonlinear systems. This approach consists of constructively
designing a control law for nonlinear systems by considering some state variables as being virtual controls, and designing intermediate control laws for them. Some internal variables are sometimes inaccessible to measurement or expensive to measure, hence the introduction of observers based on the same principle.
Finally, an application of this approach on a multi-input / multi-output nonlinear system, represented by an induction motor, was made. This procedure makes it possible to obtain in an instructive way a control law which ensures the stability of the closed loop system by presenting remarkable dynamic performances as well as a good robustness vis-à-vis the deviations of the parameters of the motor.

The main purpose of this paper is to exploit the "BACKSTEPPING" technique based on the Lyapunov theory for non-linear multi-input / multi-output system control, represented by a doubly fed induction machine. This approach consists of constructively designing a control law for nonlinear systems by considering some state variables as virtual controls, and designing them intermediate control laws. The Backstepping control makes it possible to obtain informatively a control law which ensures the stability of the closed-loop system by presenting remarkable dynamic performances as well as a good robustness with respect to the deviations of the parameters of the engine.

In this document, we will present a control technique called control by type-1 fuzzy logic, this control makes it possible to instantly keep independent control of the active and reactive powers generated by doubly fed induction generator (DFIG) in a wind energy production system coupled to the grid. This resulted in a high yield and optimum production quality. In the first part we presented the individual modeling of the wind chain that is composed of a DFIG driven by a turbine with variable pitch of the blades to control the capture of energy from the wind during its low and high speeds. This machine is directly coupled to the grid by the stator and controlled by the rotor quantities through two bidirectional PWM converters. The main function of these converters is the connection of the wind generator to the power grid in two different ways: one on the grid side converter which will allow continuous bus control and improve the power factor on the grid side; the other, on the rotor side converter which will allow the application of our control technique to control and optimize the energy flow generated by the stator of our machine in our system. Finally, we will present the results of simulations which show the effectiveness of this command.

Nowadays, several works have been oriented towards the study of the doubly-fed induction motor "DFIM", which is a three-phase asynchronous machine with a wound rotor supplied by two voltage sources, one at the stator and the other at the rotor. The latter and thanks to the development of power electronics equipment and the appearance of modern control techniques present an ideal solution for high power and variable speed drives.
The control of this motor is a delicate operation because this motor is characterized by a nonlinear dynamic, with time-varying parameters and with a strong coupling between the magnetic behavior and the mechanical part. To this end, for a long time, significant efforts have been made to develop highperformance controls to control the dynamic behavior of this motor.
Fuzzy logic is an important development registered during the last two decades. This makes it possible to obtain an adjustment law that is often very effective without having to carry out in-depth modeling. As opposed to a standard regulator or a state feedback regulator, the fuzzy logic regulator does not deal with a well-defined mathematical relation, but uses inferences with several rules, based on linguistic variables. We propose in this work an association combining the type-2 fuzzy logic with the oriented stator flux vector control of DFIM to achieve a more efficient control by taking advantage of the advantages offered by each of them these techniques.

In this work, we develop a new hybrid algorithm between two control techniques namely: sliding mode control and fuzzy logic control to instantly keep an independent, precise and continuous control of mechanical power (speed, torque) produced by the permanent magnet synchronous machine and to improve tracking qualities with zero static error and to ensure robustness with guaranteed stability. This resulted in a high yield and optimum production quality. In the first part we presented the modeling of this machine and their PWM bidirectional converters. The main function of these converters is the connection of the machine to the electrical grid in two different ways: one on the grid side converter which will allow continuous bus control and improve the power factor on the grid side; the other, on the converter on the stator side which will allow the control and optimization of the mechanical energy flow generated by this machine. To do this, we will develop the fuzzy sliding hybrid control based on estimated gains and fuzzy regulators to eliminate the chattering phenomenon, the disadvantage of the sliding control, and converge these errors toward zero and thus ensure the stability of this machine. the disadvantage of fuzzy logic control.
The numerical simulation results obtained during the application of the fuzzy sliding hybrid control on our machine show the effectiveness of this implemented control.

In this work is developed a control algorithm is called the 2nd order sliding mode control known for its simplicity and robustness on a WPCS based on a DFIG to keep instantaneous independent, accurate and continuous control of active and reactive power generated by our system and improve the tracking qualities with zero static error and ensure robustness with a guaranteeing stability. This allowed obtaining a high efficiency and an optimal production quality. In the first part we presented the modeling of the wind chain that is composed of a DFIG driven by a turbine with variable blade pitch to control the energy capture of the wind during its low and high speeds. This machine is coupled directly to the grid through the stator and driven by the rotor values through two bi-directional PWM converters. The main function of these converters is the connection of the wind generator to the grid in two different ways: one on the grid side converter that will allow the control of the DC bus and improve the power factor on the grid side; the other on the rotor side converter that will allow the application of our control technique to the control and optimization of the energy flow generated by the stator. To do this, we will develop the sliding control of order 2 based on estimated gains of order 2 to eliminate the phenomenon of chattering, and converge these errors to zero and thus ensure the stability of our system control.

This paper presents a comparative study of sliding mode control, hybrid sliding type-1 fuzzy logic and hybrid sliding type-2 fuzzy logic applied on the permanent magnet synchronous machine (PMSM). We used different criteria in this comparison: qualitative, quantitative and robust during the transient and permanent operation of the system. In this article, we present a new sliding mode control strategy applied to the PMSM, this control combines sliding mode and fuzzy logic (type-1 and type-2) to find robust control. The control proposed keeping the part of the equivalent control by sliding mode and will change the part of the switching by a fuzzy controller. Simulation results with a sliding mode control, type-1 fuzzy logic controller (T1FLC) and with an interval type-2 fuzzy logic controller (IT2FLC) of a permanent magnet synchronous machine are presented. The advantage of using interval type-2 fuzzy logic controller is verified.

In this work is developed a hybrid algorithm enter two control techniques namely: sliding mode and fuzzy logic to keep instantaneous, independent, accurate and continuous control of active and reactive power generated by WECS based on a doubly fed induction generator (DFIG) and improve the tracking qualities with zero static error and ensure robustness with a guarantee stability. This allowed obtaining a high efficiency and an optimal production quality. In the first part we presented the individual modeling of the wind chain that is composed of a DFIG driven by a turbine with variable blade pitch to control the energy capture of the wind during its low and high speeds. This machine is coupled directly to the grid through the stator and driven by the rotor magnitudes through two bi-directional PWM converters. The main function of these converters is the connection of the wind generator to the grid in two different ways: one on the grid side converter that will allow the DC bus control and improve the power factor on the grid side; the other on the rotor side converter that will allow the control and optimization of the energy flow generated by the stator of our system. To do this, we will develop the hybrid fuzzy sliding control based on estimated gains and fuzzy controllers to eliminate the phenomenon of chattering the disadvantage of the sliding control, and converge these errors to zero and thus ensure the stability of the system the disadvantage of the fuzzy logic control.

In this work, we present a new comparative study between two control techniques, namely vector control and fuzzy logic control, in order to highlight the efficiency and robustness of each of them, this study is based on three essential criteria: qualitative, quantitative and robustness carried out during the transient and permanent operations of our wind energy conversion system which is based on a double fed induction generator driven by a turbine with variable blade pitch, and controlled through the rotor variables by two bidirectional converters. In the first part we presented the individual modeling of the wind chain, then we presented and developed the commands necessary to control the active and reactive powers produced by this system. Finally, we were interested in the comparative study between the proposed commands. The results obtained show that fuzzy logic control is the most efficient and effective control on the wind energy conversion system considered compared to vector control, namely:
Qualitative comparison: This comparison is based on the observation of simulation results obtained by applying the two commands developed on our system. The proposed active and reactive power setpoints are given in the form of steps while the generator is driven at a fixed speed. The observation of the simulation results shows that the two powers follow their new references in the two types of controls; however, the response time, overshoot and oscillations of the controlled quantities, as well as the exponential convergence of the errors for the transient state and the change of the setpoints are different. It is noted that the best values of the latter are the values obtained during the application of the fuzzy logic control , which can be considered as the most efficient control compared to the vector control.
Quantitative comparison: The target of this test is to compare the two controls quantitatively (in numbers); to highlight the performance of each of them. The valuesof the static error J1 and that of the necessary command J2 are calculated in the time interval [0s 5s]. The simulation results presented clearly show that fuzzy logic control is the most efficient from the point of view of minimizing the energy criterion which gives us the lowest values (J1 = 3.3360e+007 for the active power, and J1 = 2.2705 e+007 for the reactive power), on the other hand the vector control which gives us the values (J1 = 2.8944e+008 for the active power, and J1 = 1.6288e+008 for the reactive power). Concerning the second precision criterion, we note that it is the fuzzy logic control which gives the lowest values (J2 = 5.0687e+004 for the active power, and J2 = 7.6097e+005 for the reactive power) on the other hand the vector control which gives us the values(J2 = 4.0734e+005 for the active power, and J2 = 7.6095e+006 for the reactive power).
Robustness comparison: In this test, we visualized the shape of the two active and reactive powers for a simulation duration Ts=5s. The two proposed controls present a high robustness and ensure good performance even in the presence of small parametric variations with external disturbances; however, control by fuzzy logic presents as the best control having almost smooth power shapes and a good followup of the setpoint shapes, on the other hand vector control which gives us remarkable ripples.

This paper focuses on the diagnosis of electrical faults in electrical drives based on the permanent magnet synchronous machine (PMSM) which is supplied by a system of voltages delivered by a voltage inverter, this is controlled by the hysteresis strategy with three reference currents. High current or cut-off can cause problems for three-phase equipment and the
most common impact of these faults is overheating of the equipment and consequently degradation of electrical insulation and reduction of service life. A modeling of the system performance in the healthy and faulty machine cases has been simulated. In this paper, firstly, the system is analyzed for the different supply current faults of types: unbalance and current break. Then, the fault detection of the permanent magnet synchronous machine can be illustrated by the evolution of the parameters that describe the electrical and mechanical characteristics of the machine. The results of the simulation are realized by Simulink MATLAB.

Les machines asynchrones sont les plus utilisées dans les secteurs industriels en raison liée au faible coût, à la masse réduit, à la robustesse, à la construction simple et à un minimum d’entretien, bien que celles-ci imposent des structures internes et des stratégies de commande plus complexes. De nos jours, plusieurs travaux ont été orientés vers l'étude de la machine asynchrone à double alimentation "MADA", qui est une machine asynchrone triphasée à rotor bobiné alimentée par deux sources de tension l’un au stator et l’autre au rotor. L’histoire de la commande des machines asynchrones a commencé en Allemagne au début des années soixante-dix avec la proposition de la théorie d’orientation du champ par Blaschke. Cette théorie a permis de résoudre le problème du découplage, par conséquent, il est devenu possible de commander séparément le flux et la vitesse (couple). Toutefois, malgré l’amélioration apportée par cette commande, certains inconvénients ont limité son utilisation dans les applications de hautes performances. En effet, elle ne peut réaliser qu’un découplage asymptotique autour d’un flux constant. En plus, l’établissement de cette commande utilise des régulateurs PI qui nécessitent une parfaite connaissance du modèle du système à régler et qui présentent une grande sensibilité aux variations paramétriques, notamment à la variation de la résistance rotorique qui a une relation directe avec l’angle d’orientation du flux. De tels inconvénients ont poussé les chercheurs vers le développement des techniques de commande non linéaire, on peut distinguer de manière non exhaustive la commande par backstepping. Elle a été développée par M. Krstic et P. V. Kokotovic, ont introduit des méthodes utilisant des changements de variables récursifs appelés backstepping, sur des classes de
systèmes triangulaires non linéaires paramétrés. De façon générale, les lois des commandes proposées, satisfont de bonnes propriétés de robustesse et d'atténuation de perturbations, mais ne s'appliquent qu'à des classes restreintes de systèmes et n'utilisent que des contrôleurs statiques. D’autre part, un important développement a été enregistré pendant les deux dernières décennies. En effet, l’apparition de nouvelles techniques, telles que : la logique floue, les réseaux de neurones, les algorithmes génétiques et d’autres, a permis de former une nouvelle discipline appelée intelligence artificielle. La logique floue est l’une des branches importantes de l’intelligence artificielle. Les bases théoriques de cette logique ont été établies en 1965 par le professeur Lotfi Zadeh à l’université de Berekley en Californie, qui introduit la notion de l’ensemble flou. Celle-ci permet d’obtenir une loi de réglage souvent très efficace sans devoir faire des modélisations approfondies. À la lumière de ce qui a été dit, nous proposons dans ce travail une association combinant la logique floue avec la commande par backstepping pour la commande de la MADA. Cette association sera exploitée pour établir de nouvelle commande robuste, à base de la logique floue, en vue d’améliorer les réponses dynamiques du moteur asynchrone à double alimentation. La commande proposée est conçue à partir de la commande par Backstepping (basée sur le principe de l'orientation du flux statorique dans le repère 𝑑,) complété par un contrôleur flou du type 1 pour améliorer la robustesse. En utilisant la théorie de stabilité de Lyapunov, on montre que les dynamiques de poursuite de trajectoire sont asymptotiquement stables. Cette technique consiste à remplacer les gains des régulations de la commande par backsteppnig par des contrôleurs flous du type 1 à une entrée est l’erreur entre la valeur mesurée et la valeur de référence.

The efficiency of a wind turbine depends primarily on the power of the wind, the power curve of the turbine and the ability of the generator to respond to fluctuations in the wind. This article then proposes a robust control strategy of the doubly-fed induction generator applied in the wind energy conversion system, the active and reactive powers, which are generated by the DFIG will be decoupled by the orientation of the stator flux. The proposed control is combined between sliding mode control and type-2 fuzzy logic, this technique is robust to the modeling uncertainties of the generator and the wind generator, and which makes it possible to optimize energy production (efficiency). Finally, the performance of the system was tested and compared by simulation in terms of follow-up of instructions and the robustness with respect to the parameter variations of the DFIG. The results obtained show the interest of such
a control in this system.

La matière a pour objectif de maîtriser les outils de représentation graphiques des systèmes automatisés (GRAFCET), installer et entretenir des éléments d’automatismes industriels, effectuer la programmation et la configuration des automates programmables.

In this article we present the vector control of the doubly fed induction machine (DFIM) fed by a PWM inverter. The oriented stator flux vector control is efficient because of the simplicity of design and implementation and allows a natural decoupling between flows and currents. The application of this strategy is achieved by using Proportional Integral (PI) Controllers. The parameters of these controllers are calculated directly from the parameters of the machine using conventional analytical methods, which require careful calculation and a good knowledge of all machine parameters. The aim of our study is to try to replace the controller (PI) for speed and flux by a fuzzy logic controller type 1. Robustness tests of the control vis-à-vis the parametric variations of the machine will be made.

In this article, we present a new sliding mode control strategy applied to the doubly fed induction machine. The proposed control combines sliding mode and fuzzy logic to achieve robust control. This technique finds its strongest justification for the problem of using a nonlinear control law robust to the uncertainties of the model. The objective of this control is improved the outputs generated by the doubly fed induction machine supply decoupled by orientation of the stator flux. Finally, the performance of the system was tested and compared by simulation in terms of follow-up of instructions, and the robustness with respect to the parametric variations of this machine. The simulation results obtained clearly show the effectiveness of this control.

In this paper, we present a new hybrid control strategy applied to the doubly fed induction generator (DFIG) used in wind energy conversion systems (WECS) is presented. The main objective of the study is to derive a control strategy which will be applied to a bidirectional converter supplying a DFIG based on the combination of sliding mode control and the fuzzy logic. This technique finds its strongest justification to the problem of using a nonlinear control robust to the uncertainties of the model. Initially, the sliding mode control was carried out which makes it possible to independently control the active and reactive power produced by the DFIG and injected in the main grid according to the power references derived from turbine’s mechanical power and the grid operator. Then, in order to improve the results, another technique will be introduced is the hybrid control between the sliding mode control and fuzzy logic (FSMC). This technique is based on the cascade control structure which combines two parts, the first is the equivalent control part (SMC) and the other is the fuzzy control part (FLC).
Finally, a comparative study will be presented between the proposed control strategy and the classic sliding control according to the robustness with respect to the parameter variations of the machine, the integral square error and the integral absolute error. The results clearly show the superiority of the proposed control compared to the sliding mode control.

The aim of this work concerns the study, modeling and control of a wind energy conversion system based on a doubly-fed induction generator (DFIG) driven by a constant speed and controlled by the rotor quantities through two converters bidirectional. For this, a modeling of the various components of this system was carried out. These models were used to develop a control technique called type 2 fuzzy logic controls to ensure precise and continuous control of the stator powers generated while ensuring stability and speed of tracking with zero static error. This resulted in high system efficiency and optimum production quality.

In this paper, we present another strategy for the vector control of the doubly fed induction motor (DFIM) .The vector control with stator-oriented flux is efficient because of the simplicity of design and implementation and allows to have a natural decoupling between flows and currents. This command is carried out using Integral Proportional Controllers (PI); the parameters of these controllers are calculated directly from the parameters of the machine using conventional analytical methods, which require careful calculation and familiarity with all machine parameters. The aim of our study is to try to replace controllers (PI) with controllers based on type 2 fuzzy logic in order to obtain robust control. Robustness tests of the control for the parameter variations of the machine will be made.

The work carried out in this article concerns the modeling and the control of a wind energy production system based on an doubly-fed induction generator driven by a constant speed, and controlled through the rotor variables by a bidirectional converter called the inverter. we modeled the wind chain separately to control the powers generated by this system, we used the type-2 fuzzy logic control based on type-2 fuzzy regulators in order to improve the quality of tracking of the electrical power produced and always d 'ensure the robustness of the system.

In this paper, we present a new sliding mode control strategy applied to the doubly fed induction machine, this control combines sliding mode and type-2 fuzzy logic to find robust control. The proposed control kept the part of the equivalent control by sliding mode and will change the part of the switching by a type-2 fuzzy controller has an input is the error between the measured value and the reference value. In this command we apply the orientation of the stator flux to have the decoupling between the flux and the current. The results obtained in simulation show the effectiveness of this command.

In this article, we present a comparative study between two control techniques applied on the Permanent Magnet Synchronous Machine (PMSM), namely vector control and fuzzy logic. This comparison is based on three criteria: qualitative, quantitative and robust during the transient and permanent operation of the system. The latter comprises a machine is driven through the stator variables by two bidirectional converters. In the first part, we have presented the individual modeling of the global chain (PMSM, Inverter, and Rectifier). Then we presented and developed the two commands techniques to control the speed and the torque produced by this machine. The results of this study made it possible to evaluate the performance of these controls.

In this article we present the vector control of the doubly fed induction machine (DFIM) fed by a PWM inverter. The oriented stator flux vector control is efficient because of the simplicity of design and implementation and allows a natural decoupling between flows and currents. The application of this strategy is achieved by using Proportional Integral (PI) Controllers. The parameters of these controllers are calculated directly from the parameters of the machine using conventional analytical methods, which require careful calculation and a good knowledge of all machine parameters. The aim of our study is to try to replace the speed controller (PI) with a fuzzy logic controller type 1. Robustness tests of the control vis-à-vis the parametric variations of the machine will be made.

In this article we present a comparative study between the two types of fuzzy logic mamdani and sugeno applied to the doubly-fed induction motor (DFIM). The proposed command combines the flow-oriented vector control and the type 1 fuzzy logic to get a robust control. The oriented stator flux vector control is efficient because of the simplicity of design and allows natural decoupling between flows and currents. The application of this strategy is carried out using Integral Proportional Controllers (PI) which are calculated directly from the machine parameters using conventional analytical methods which need a careful calculation and a good knowledge of all machine settings. The aim of our study is to try to replace the speed control controller (PI) with a type 1 fuzzy logic controller (mamdani or sugeno). Robustness tests of the control with respect to the parametric variations of the machine will be carried out.

In this article, we present a comparative study between two control techniques applied on the Permanent Magnet Synchronous Machine (PMSM), namely vector control and fuzzy logic. This comparison is based on three criteria: qualitative, quantitative and robust during the transient and permanent operation of the system. The latter comprises a machine is driven through the stator variables by two bidirectional converters. In the first part, we have presented the individual modeling of the global chain (PMSM, Inverter, and Rectifier). Then we presented and developed the two commands techniques to control the speed and the torque produced by this machine. The results of this study made it possible to evaluate the performance of these controls.

This paper presents the design of a new nonlinear control for the doubly fed induction machine (DFIM). The proposed control is based on a Backstepping type control technique supplemented by a type 1 fuzzy controller to improve its robustness. Using the Lyapunov stability theory, it is shown that trajectory tracking dynamics are asymptotically stable. In order to simplify the control, we apply the control by orientation of the stator flux which has the advantage of having a decoupling between the flow and the current. The simulation results show the quality of the proposed control despite parametric uncertainties.

In engineering, the simulation is an effective and economical means commonly used to make preliminary studies and / or comparative, both in development (design), and during normal system operation. Currently, several simulation tools, including MATLAB / SimulinkTM are used in industry and in academia. In this work, we present the principle of modeling and simulation of an electrical machine: the asynchronous motor squirrel cage. The latter, thanks to the many benefits it provides over other types of electric motors, has become the engine of choice in industrial processes.

Cet article présente l’implémentation de l’algorithme RSA sur FPGA de la famille Virtex-2. En premier lieu, nous avons implémenté l’algorithme de Montgomery parallèle à deux CSA et l’algorithme qui basé sur le calcul du complément à deux de la partie inférieur de la multiplication. Ensuite nous avons apporté une amélioration de ce dernier par une multiplication basée sur le codage de Booth modifié. Cet algorithme modifié a permit d’améliorer les performances en débit. Finalement nous avons implémenté l’algorithme RSA pour les différentes architectures de la multiplication de Montgomery.

Cet article présente l’implémentation de l’algorithme RSA sur FPGA de la famille Virtex-2. En premier lieu, nous avons implémenté l’algorithme de la multiplication modulaire de Montgomery à deux CSAs et l’algorithme proposé par O. Nibouche. Ensuite nous avons apporté une amélioration de ce dernier par la modification de la multiplication classique par une multiplication basée sur le codage de Booth modifié. Cet algorithme modifié a permit d’améliorer les performances en débit. Finalement nous avons implémenté le chiffrement RSA pour les algorithmes sus cités sur un circuit reconfigurable FPGA.

Cet article présente l’implémentation de l’algorithme RSA sur FPGA de la famille Virtex-2. En premier lieu, nous avons implémenté l’algorithme de la multiplication modulaire de Montgomery à deux CSAs et l’algorithme proposé par O. Nibouche. Ensuite nous avons apporté une amélioration de ce dernier par la modification de la multiplication classique par une multiplication en base 4. Cet algorithme modifié a permit d’améliorer les performances en débit. Finalement nous avons implémenté le chiffrement RSA pour les algorithmes sus cités sur un circuit reconfigurable FPGA.

Cet article présente l’implémentation de l’algorithme RSA sur FPGA de la famille Virtex-2. En premier lieu, nous avons implémenté l’algorithme de la multiplication modulaire de Montgomery à deux CSAs et l’algorithme proposé par O. Nibouche. Ensuite nous avons apporté une amélioration de ce dernier par la modification de la multiplication classique par une multiplication en base 4. Cet algorithme modifié a permit d’améliorer les performances en débit. Finalement nous avons implémenté le chiffrement RSA pour les algorithmes sus cités sur un circuit reconfigurable FPGA.

Cet article présente l’implémentation de l’algorithme RSA sur FPGA de la famille Virtex-2. En premier lieu, nous avons implémenté l’algorithme de la multiplication modulaire de Montgomery à deux CSAs et l’algorithme proposé par O. Nibouche. Ensuite nous avons apporté une amélioration de ce dernier par la modification de la multiplication classique par une multiplication en base 4. Cet algorithme modifié a permit d’améliorer les performances en débit. Finalement nous avons implémenté le chiffrement RSA pour les algorithmes sus cités sur un circuit reconfigurable FPGA.

This paper presents an implementation of various algorithms about Montgomery multiplication on a FPGA (Virtex-2 family). First, we have implemented the Montgomery algorithm with two CSAs and the modified algorithm of O. Nibouche in parallel and serial. After that, we have introduced a modification on Montgomery multiplication by introducing a modified Booth
recoding. The modified algorithm improves significantly the performance in Area/Time.

In this paper, a novel field-oriented induction motor drive using backstepping control design is presented. Backstepping control is proposed for replacing the existing PI controller to obtain high performance motion control systems, for the speed, flux and currents control loops. Stability analysis based on Lyapunov theory is also performed to guarantee the convergence of the speed tracking error from all possible initials conditions. Also, the computer simulations confirm that the proposed backstepping control scheme offers improved performance in terms of the trajectory tracking ability to time-varying reference input and robustness against parameters variation.