Introduction. Budget constraints in a world ravenous for electrical power have led utility companies to operate generating stations with full power and sometimes at the limit of stability. In such drastic conditions the occurrence of any contingency or disturbance may lead to a critical situation starting with poorly damped oscillations followed by loss of synchronism and power system instability. In the past decades, the utilization of supplementary excitation control signals for improving power system stability has received much attention. Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp low-frequency oscillations caused by load disturbances or short-circuit faults.

Problem. Adaptive power system stabilizers have been proposed to adequately deal with a wide range of operating conditions, but they suffer from the major drawback of requiring parameter model identification, state observation and on-line feedback gain computation. Power systems are nonlinear systems, with configurations and parameters that fluctuate with time that which require a fully nonlinear model and an adaptive control scheme for a practical operating environment. A new nonlinear adaptive fuzzy approach based on synergetic control theory which has been developed for nonlinear power system stabilizers to overcome above mentioned problems.

Aim. Synergetic control theory has been successfully applied in the design of power system stabilizers is a most promising robust control technique relying on the same principle of invariance found in sliding mode control, but without its chattering drawback. In most of its applications, synergetic control law was designed based on an asymptotic stability analysis and the system trajectories evolve to a specified attractor reaching the equilibrium in an infinite time. In this paper an indirect finite time adaptive fuzzy synergetic power system stabilizer for damping local and inter-area modes of oscillations for power systems is presented. 

Methodology. The proposed controller design is based on an adaptive fuzzy control combining a synergetic control theory with a finite-time attractor and Lyapunov synthesis. Enhancing existing adaptive fuzzy synergetic power system stabilizer, where fuzzy systems are used to approximate unknown system dynamics and robust synergetic control for only providing asymptotic stability of the closed-loop system, the proposed technique procures finite time convergence property in the derivation of the continuous synergetic control law. Analytical proofs for finite time convergence are presented confirming that the proposed adaptive scheme can guarantee that system signals are bounded and finite time stability obtained. 

Results. The performance of the proposed stabilizer is evaluated for a single machine infinite bus system and for a multi machine power system under different type of disturbances. Simulation results are compared to those obtained with a conventional adaptive fuzzy synergetic controller.

L’article décrit la conception et la mise en øe}uvre en temps réel d’une commande non linéaire appliquée à un système de conversion de l’énergie éolienne (SCEE). La commande backstepping a été mise en øe}uvre pour améliorer les performances du système de conversion éolienne basé sur un générateur synchrone à aimants permanents (PMSG) connecté au réseau. Deux convertisseurs statiques assurent la connexion au réseau et sont contrôlés par la modulation de largeur d’impulsion (MLI). L’algorithme de contrôle proposé assure un contrôle de vitesse adéquat pour extraire la puissance maximale. Une description détaillée des lois de contrôle du backstepping basées sur la technique de stabilité de Lyapunov a été exposée. Les résultats obtenus par l’application de cette approche ont clairement répondu aux exigences de robustesse et de suivi des références même dans des conditions de vent fluctuants, et ont confirmé l’efficacité d’un tel contrôle dans les modes de fonctionnement statique et dynamique.

L’article décrit la conception et la mise en øeuvre en temps réel d’une commande non linéaire appliquée à un système de conversion de l’énergie éolienne (SCEE). La commande backstepping a été mise en øeuvre pour améliorer les performances du système de conversion éolienne basé sur un générateur synchrone à aimants permanents (PMSG) connecté au réseau. Deux convertisseurs statiques assurent la connexion au réseau et sont contrôlés par la modulation de largeur d’impulsion (MLI). L’algorithme de contrôle proposé assure un contrôle de vitesse adéquat pour extraire la puissance maximale. Une description détaillée des lois de contrôle du backstepping basées sur la technique de stabilité de Lyapunov a été exposée. Les résultats obtenus par l’application de cette approche ont clairement répondu aux exigences de robustesse et de suivi des références même dans des conditions de vent fluctuants, et ont confirmé l’efficacité d’un tel contrôle dans les modes de fonctionnement statique et dynamique.

L'article décrit la conception et la mise en œuvre en temps réel d'une commande non linéaire appliquée à un système de conversion de l'énergie éolienne (SCEE). La commande backstepping a été mise en œuvre pour améliorer les performances du système de conversion éolienne basé sur un générateur synchrone à aimants permanents (PMSG) connecté au réseau. Deux convertisseurs statiques assurent la connexion au réseau et sont contrôlés par la modulation de largeur d'impulsion (MLI). L'algorithme de contrôle proposé assure un contrôle de vitesse adéquat pour extraire la puissance maximale. Une description détaillée des lois de contrôle du backstepping basées sur la technique de stabilité de Lyapunov a été exposée. Les résultats obtenus par l'application de cette approche ont clairement répondu aux exigences de robustesse et de suivi des références même dans des conditions de vent fluctuants, et ont confirmé l'efficacité d'un tel contrôle dans les modes de fonctionnement statique et dynamique.

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.

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.

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.

Anti-lock Braking System (ABS) is used in automobiles to prevent slipping and locking of wheels after the brakes are applied. Its control is a rather complicated problem due to its strongly nonlinear and uncertain characteristics. The aim of this paper is to investigate the wheel slip control of the ground vehicle, comprising two new strategies. The first strategy is the Sliding Mode Controller (SMC) and the second one is the Fuzzy Sliding Mode Controller (FSMC), which is a combination of fuzzy logic and sliding mode, to ensure the stability of the closed-loop system and remove the chattering phenomenon introduced by classical sliding mode control. The obtained simulation results reveal the efficiency of the proposed technique for various initial road conditions.

This paper presents the particle swarm optimization (PSO) algorithm in conjuction with the fuzzy logic method in order to achieve an optimized tuning of a proportional integral derivative controller (PID) in the DTC control loops of dual star induction motor (DSIM). The fuzzy controller is insensitive to parametric variations, however, with the PSO-based optimization approach we obtain a judicious choice of the gains to make the system more robust. According to Matlab simulation, the results demonstrate that the hybrid DTC of DSIM improves the speed loop response, ensures the system stability, reduces the steady state error and enhances the rising time. Moreover, with this controller, the disturbances do not affect the motor performances.

This paper designs an indirect power control method for brushless doubly fed induction generator (BDFIG), in which the stator is attached to grid with back-to-back space vector modulation (SVM) converter that converts the generated wind power. Our control method is a sliding mode control based on the theory of variable structure control. Specifically, the active and reactive powers, which are exchanged between the stator of the BDFIG and the grid in a linear and decoupled manner, are subjected to decoupled, vector control. In addition, a proportional integral (PI) controller was implemented to keep the DC-voltage constant for the back-to-back SVM converter. The efficiency of our control strategy was validated through simulation. The research greatly promotes the control of renewable energy generators.

This paper deals with the robust power control of a grid-connected brushless doubly-fed induction generator (BDFIG) driven by the variable speed wind turbine. With the using of a super twisting algorithm which is a high-order sliding mode controller (HOSMC). This approach guarantees both the dynamic performance and the same robustness as traditional first order (SMC) algorithm and reduces the chattering phenomenon, which is the biggest disadvantage in the implementation of this technique. The developed algorithm relies on the decoupling control by implementing the strategy of oriented grid flux vector control. In order to enhance the desired performances, an attempt is made by controlling the generated stator active and reactive powers in a linear and decoupled manner to ensure the global asymptotical stability, HOSMC approach is implemented. Therefore, an optimal operation of the BDFIG in sub-synchronous operation is used in addition to the stator power flows where the stator power factor is kept in a unity. The suggested method is examined with the Matlab/Simulink software. The performances and the feasibility of the designed control are illustrated by simulation results.

This paper designs an indirect power control method for brushless doubly fed induction generator (BDFIG), in which the stator is attached to grid with back-to-back space vector modulation (SVM) converter that converts the generated wind power. Our control method is a sliding mode control based on the theory of variable structure control. Specifically, the active and reactive powers, which are exchanged between the stator of the BDFIG and the grid in a linear and decoupled manner, are subjected to decoupled, vector control. In addition, a proportional integral (PI) controller was implemented to keep the DC-voltage constant for the back-to-back SVM converter. The efficiency of our control strategy was validated through simulation. The research greatly promotes the control of renewable energy generators.

This paper deals with the robust power control of a grid-connected brushless doubly-fed induction generator (BDFIG) driven by the variable speed wind turbine. With the using of a super twisting algorithm which is a high-order sliding mode controller (HOSMC). This approach guarantees both the dynamic performance and the same robustness as traditional first order (SMC) algorithm and reduces the chattering phenomenon, which is the biggest disadvantage in the implementation of this technique. The developed algorithm relies on the decoupling control by implementing the strategy of oriented grid flux vector control. In order to enhance the desired performances, an attempt is made by controlling the generated stator active and reactive powers in a linear and decoupled manner to ensure the global asymptotical stability, HOSMC approach is implemented. Therefore, an optimal operation of the BDFIG in sub-synchronous operation is used in addition to the stator power flows where the stator power factor is kept in a unity. The suggested method is examined with the Matlab/Simulink software. The performances and the feasibility of the designed control are illustrated by simulation results.