Keywords: Estimations and identification, Time-delay systems, Control applications
Abstract: This paper deals with a new parameter estimation method for an ultra-local model of Broïda. The proposed approach is based on the algebraic derivation techniques and the linear system resolution method, in order to estimate the ultra-local model parameters, such that the variable time-delay. The closed-loop control is achieved via an adaptive PI controller to reject the influence of noises and disturbances. A simulation results of a thermal process application are given to validate the effectiveness of the proposed strategy. A performance comparison with a classical PID controller is achieved.

Keywords: Fuzzy and neural systems, Intelligent and AI based control, Time-delay systems
Abstract: Due to the great effect of initial parameterization on the accuracy of approximation result, when a Fuzzy Wavelet Neural Network (FWNN) is used for system identification, the number of sufficient fuzzy rules, the number of needed wavelet functions and the initial values of structure parameters have to be correctly determined. The aim of this paper is to present a new efficient method for determination of all these network parameters. Based on the powerful properties of wavelets: the time-scale distribution of wavelet energy and the admissibility of wavelet kernels, we present a method for initial parameterization of FWNN. Taking nonlinear dynamical systems with longer input delays as simulated example, a comparative study is done in order to prove the effectiveness of the proposed method. It is seen that the proposed initialization method achieves higher accuracy and has good performance compared to other techniques.

Keywords: Time-delay systems, Linear and nonlinear systems, Modeling and simulation
Abstract: The paper investigates the stability problem for linear singular discrete time-delay systems. Using discrete Lyapunov-like functions, new stability criteria are derived in terms of strict linear matrix inequality, which guarantees the system to be regular, causal and finite-time stable. A computer simulation was performed for the analysis of the dynamical behavior of this system.

Keywords: Time-delay systems, Modeling and simulation, Linear and nonlinear systems
Abstract: This paper is concerned with the problem of finite- time stability of a class of discrete-time singular system with time-delay and nonlinear perturbations. By using discrete Lyapunov function approach, new stability criterion is derived in terms of strict linear matrix inequality to guarantee the system to be regular, causal and finite-time stable. A numerical example is provided to illustrate the effectiveness of the proposed method.

Keywords: Control applications, Estimations and identification, Modeling and simulation
Abstract: In this paper, we propose an unknown input estimation based sliding mode control (UIESMC) approach for air path in the EGR-VGT diesel engine. This proposed UIESMC controller is adopted to track the intake and exhaust manifold pressures, and compressor mass flow rate when under unknown inputs, which include the un-modeled dynamics, modeled parametric uncertainties and the unknown faults. These unknown inputs are estimated by PI observer by applying high gain at the integral term to satisfy the requirements of both estimation accuracy and less sensitivity to measure noises. This paper finally inverted the EGR and VGT gas mass flow rates into their corresponding valves positions by flow-position transformation module. Finally, through co-simulation results from AMESim and MATLAB/Simulink, the effectiveness and robustness of the proposed control strategy is demonstrated.

Keywords: Control applications, Fault detection and Diagnostics, Industrial control
Abstract: This paper describes the synthesis of a fault tolerant control (FTC) of 3-phase squirrel cage induction machine. Indirect Rotor Field Oriented Control (IRFOC) was combined to robust sliding mode control (SMC). The sliding mode technique is used to reject modeling uncertainties, internal and external disturbances. The controlled induction machine will be forced to a sliding surface and the behavior of the machine slides to the desired equilibrium point, particularly in faulty conditions. We take as an example the stator inter-turn fault which can be modeled using the Winding Function Theory (WFT). Simulation results show the applicability and the tolerance of the proposed control scheme.

Keywords: Control applications, Fuzzy and neural systems, Linear and nonlinear systems
Abstract: This paper deals with an application of saturated LMI approach to a DC-DC buck converter widely used in photovoltaic generators. Stability and tracking problems of Takagi-Sugeno (T-S) fuzzy positive systems are studied. Positivness in closed loop and constraints are introduced in the design phase. Hence, theoretical results are applied to the DC-DC buck converter. Based on simulation results success of the method is shown for this application.

Keywords: Control applications, Fuzzy and neural systems, Modeling and simulation
Abstract: The spray under pressure is an effective save on water. This task should be automated and controlled in order to limit the water waste and the facilities of damages. For this reason,we find a mathematical model describing the irrigation process with the Takagi-Sugeno fuzzy model approach and the clustering technique. This paper presents the synthesis of a hybrid control applied to the station of irrigation by sprinkling, Based on the combination of the fuzzy logic approach and the PI controller, this method has the advantage of combining the performance of both controllers. A fuzzy supervisor manages the switching from one to another and regulates the rate of participation of each order. After presentation of mathematical model of our station, simulation results illustrate the performance of the control strategy.

Keywords: Control applications, Linear and nonlinear systems, Modeling and simulation
Abstract: In this paper we develop a nonlinear controller based on sum of squares decomposition applied to turbocharged biodiesel engine. The basic idea is to employ polynomial Lyapunov function in order to formulate the stability sufficient conditions in the terms of state dependent matrix inequalities. The obtained controller gain regulates the flows for the Variable Geometry Turbocharger and the Exhaust Gas Recirculation systems in order to minimize the NOx emission and the smoke of diesel engine. SOS-based control has been simulated on experimental biodiesel testbed shows the effectiveness of this approach.

Keywords: Autonomous Ssystems, Intelligent and AI based control, Estimations and identification
Abstract: The fuzzy clustering model makes up one of the best approaches to show an excellent ability to identify and model nonlinear systems. In literature, several algorithms were used to solve this kind of case. Fuzzy c-means (FCM) is one of the most used clustering methods because it is efficient, straightforward, and easy to implement. However, the FCM has its weakness for example, the algorithm is generally sensitive to initialization and is easily trapped in local optima due to its non-convex objective function. To avoid these problems, heuristic methods introduced by many researchers such as particle swarm optimization (PSO). So, it is a robust strategy for optimization problem. In this paper, a fuzzy clustering method based on FCM and PSO is study which make use of the merits of both algorithms to find a new model of the irrigation station. Experimental results applied to station of irrigation show that the hybrid algorithm (FCM-PSO) is efficient and can reveal encouraging results.Our analysis indicates that the PSO improves the performance of the fuzzy c-means (FCM) algorithm.

Keywords: Bond graphs, Estimations and identification, Modeling and simulation
Abstract: the identification of the current mode is a necessary property for the hybrid systems. In several cases it is difficult to recognize the current mode. So the modes discernability becomes an important issue which necessitates more attention. In fact, this property is discussed previous for hybrid system modeled by hybrid automaton. This paper aim to extend the discernability‘s condition for another model of hybrid system which is the hybrid bond graph. The originality of this work consists of the adaptation of the discernability‘s condition to the graphical feature of bond graph modeling.

Keywords: Estimations and identification, Fuzzy and neural systems, Linear and nonlinear systems
Abstract: This paper is devoted to the stabilization of positive Takagi-Sugeno (T-S) systems with unmeasurable premise variables in the continuous case. More precisely, two approaches have been presented. The first approach is based on a representation of the estimation error by that of the case where the decision variables are measurable but affected by disturbance. In the second approach, the expression of the estimation error involves the bound of the state variables’ vector and the bound of the input vector. An application example is designed to illustrate the results and compare the effectiveness of both approaches.

Keywords: Estimations and identification, Industrial control, Linear and nonlinear systems
Abstract: Because of the dependence of the parameters in the chemical reactor industries to the raw material used in processes, an online identification of the process parameters is necessary to adjust the process control loops. This paper deals with continuous time and delay system identification of the chemical reactor. The identification of linear and single input-single output (SISO) system is based on the least square (LS) method, in which the output is corrupted by a non gaussian white noise sequence. The least square method is perhaps the most commonly used parametric identification method, but it is biased even for a white measurement noise. To remove this bias we use the instrumental variable (IV) method. Results obtained indicate that the proposed algorithm provides more accurate estimated parameters.

Keywords: Estimations and identification, Linear and nonlinear systems, Mathematical systems theory
Abstract: In nonlinear system identification, block-oriented models such as Wiener and Hammerstein models have the advantage that they are quite simple to understand and easy to use. This paper presents a structural estimation of the Wiener- Hammerstein model, which is a block-oriented model where a static nonlinear system is surrounded by two linear dynamics at its input and output. The first part concerns the estimation of the order that is made by the ratio method of determining (DR). The second part describes the problem of estimating the delay. In this sense, estimation method is proposed namely estimation algorithm RLSVT. The analytical results are validated by numerical simulation examples.

Keywords: Fault detection and Diagnostics, Embedded Systems, Autonomous Ssystems
Abstract: This paper presents a fault diagnosis system of the chaser reaction wheels used during the rendez-vous phase of the Mars Sample Return (MSR) mission. The principal component analysis has been adopted to estimate the relationships between the various variables of the process. To ensure the feasibility of the proposed FDI approach, a set of data provided by an industrial "high-fidelity" simulator of the MSR and representing the rotation rates of the spacecraft reaction wheels has been considered. The test results demonstrate that the fault detection and isolation are successfully accomplished.

Keywords: Fault detection and Diagnostics, Estimations and identification
Abstract: This paper considers the problem of simultaneous actuator and sensor faults reconstruction approach study for a class of uncertain Lipschitz nonlinear systems. This approach is used to reconstruct both actuator and sensor faults when this later is transformed into pseudo-actuator faults by introducing a simple filter. The main contribution is to develop a Sliding Mode Observer (SMO) to solve the problem of simultaneous faults. A sufficient stability conditions are achieved with Hinfini performances by solving the convex multiobjective optimisation problem. Simulation example is given to illustrate the proposed SMO performances of both states, actuator and sensor faults estimation.

Keywords: Fault detection and Diagnostics, Linear and nonlinear systems, Control applications
Abstract: This paper presents an active fault tolerant control (FTC) strategy for induction motor drive that ensures trajectory tracking and offset the effect of the sensor faults.The proposed approach consider a time varying fault that takes into account a large class of sensor fault.The physical model of induction motor is approximated by the Takagi-Sugeno (T-S) fuzzy technique in the synchronous d-q frame rotating with field-oriented control strategy. The performances of the trajectory tracking are analyzed using the Lyapunov theory and L2 optimization. Finally, the effectiveness of the proposed strategy have been illustrated in simulation results.

Keywords: Fault detection and Diagnostics, Modeling and simulation, Mathematical systems theory
Abstract: In the context of aircraft engineering and maintenance, No Fault Found (NFF) is a chain of events that develops from a pilot experiencing a system malfunction with post-flight maintenance failing to reproduce the reported symptoms. Without any repair being undertaken, the malfunction may be experienced again on subsequent flights. This present significant cost impacts to the industry that includes financial, reduced operational achievement, airworthiness challenges and potential flight safety issues. One of the major causes identified for NFF occurrence within electronic, mechanical and hydraulic products are faults that are intermittent in nature. This makes it difficult to use systematic fault detection techniques effectively, as system are subject to unknown disturbances and model uncertainties. The philosophy behind this criterion is that the designed model-based Fault Detection (FD) observer should be robust to disturbances but sensitive to intermittent faults where the occupance of intermittent faults can be alarmed by the use of an adaptive threshold. The aim of this paper is to demonstrate the development of such methodologies and to examine its performance in a real-world test bed. The test bed consists of an aircraft fuel system simulation rig which simulates by hardware the components of an aircraft fuel system.

Keywords: Estimations and identification, Fault detection and Diagnostics
Abstract: Prognostic activity deals with prediction of the remaining useful life (RUL) of physical systems based on their actual health state and their using conditions. RUL estimation gives operators a potent tool in decision making by quantifying how much time is left until functionality is lost. In addition, it can be used to improve the characterization of the material proprieties that govern damage propagation for the structure being monitored. RUL can be estimated by using three main approaches, namely model-based, data-driven and hybrid approaches. The prognostics methods used later in this paper are hybrid and data-driven approaches, which employ the Particle Filter in the first one and the autoregressive integrated moving average in the second. The performance of the suggested approaches is evaluated in a comparative study on data collected from lithium-ion battery of hybrid electric vehicle.

Keywords: Fault detection and Diagnostics, Linear and nonlinear systems
Abstract: This paper proposes a novel index to detect a sensor fault based on principal component analysis (PCA). The main idea behind this index is to evaluate similarity between Principal Components that represent a normal behavior of a system and a new that represent current function. This index is evaluated on a numerical example and the results are satisfactory

Keywords: Autonomous Ssystems, Motion control, Fuzzy and neural systems
Abstract: Genetic algorithms are used in the present work to tune the control parameters of a mini-UAV (unmanned aerial vehicle) quad-rotor. The control system consists of; two Mamdani-type fuzzy controllers for both longitudinal and lateral flight modes, and four PID controllers used to control the roll, pitch, yaw angles and the altitude. Genetic algorithms are used to optimize and adapt the parameters value of the proportional, integration and derivation gains of the four PID controllers. The designed control system and the tuning phase are tested via simulation where it shows that the designed control system using genetic algorithms exhibit good performance.

Keywords: Fuzzy and neural systems, Optimization, Linear and nonlinear systems
Abstract: Quadratic approach for the stability analysis o multi-models such as Takagi-Sugeno fuzzy systems leads in many cases to conservative results. However, it is shown that nonquadratic approach was an alternative to properly reduce the conservatism and to give more relaxations to the stability and stabilization conditions of fuzzy systems. This paper presents firstly some relaxed stabilization conditions based on common quadratic Lyapunov function (CQLF) and secondly a nonquadratic approach based on fuzzy Lyapunov function (FLF) and focused on the time-derivative of fuzzy membership functions (TDFMF). Sufficient stabilization conditions based on linear matrix inequalities (LMIs) optimization are derived to nonlinear fuzzy controller design. Finally, simulation results are given to demonstrate the effectiveness of the TDFMF-based nonquadratic approach.

Keywords: Fuzzy and neural systems, Control applications
Abstract: In this paper, observer-based indirect adaptive fuzzy controller with sliding mode observer is proposed for a class of uncertain nonlinear systems. Using fuzzy logic systems to approximate the unknown nonlinear functions, which are constructed by the state variables, if they are not available, a sliding mode observer is used to estimate the state. Thus, a combination between an adaptive fuzzy control and sliding mode observer is proposed to make sure that the state estimation converges to the state variable. The stability of the whole closed-loop systems can be guaranteed by using Lyapunov stability theorem. To verify the proposed method, a simulation results are given with application on an inverted pendulum.

Keywords: Fuzzy and neural systems, Linear and nonlinear systems, Control applications
Abstract: This paper presents a nonlinear observer-based on Takagi-Sugeno(T-S)fuzzy controller design approach for induction motor (IM). The peculiarity of this paper is the synthesis of a mono- Luenberger observer for highly coupled system. The T–S fuzzy model is firstly used to approximate the nonlinear IM systems. Next, based on the differential mean value theorem combined to the sector nonlinearity transformation, a nonlinear fuzzy observer is designed to estimate the system states in order to implement the fuzzy controller. Then, the parallel distributed compensator (PDC) scheme is used to design the fuzzy controller for the overall system. Fuzzy Controller and observer gains are obtained by solving a set of Linear Matrix Inequality (LMI).Finally, illustrative simulation results represented to validate the performance of the proposed approach.

Keywords: Fuzzy and neural systems, Modeling and simulation, Optimization
Abstract: This paper proposes a novel metaheuristic optimization algorithm called Cuckoo Search CS to extract T-S model. In this study, the structure and parameters of the fuzzy model are encoded into a particle. Thus, the optimal structure and parameters are achieved simultaneously. The proposed method was compared with the particle swarm optimization PSO through a modelling problem. The results prove that CS method represents a powerful search approach and an effective optimization technique especially in the mean of MSE and number of rules.

Keywords: Power systems, Modeling and simulation
Abstract: This study proposes a comparative analysis between the performances of the star windings and open-end stator windings of the synchronous machines with wound rotor without damper windings. The advantages of the open-end stator windings at the level of the THD voltage and the torque undulation are presented. It is shown that the novel dual open-end stator windings synchronous machine has significant benefit at the level of the power segmentation is shown.

Keywords: Power systems, Networks optimization, Linear and nonlinear systems
Abstract: The interconnections between the national power systems was developed parallel to networks of each country. Originally, the interconnections used to get outside help in case of failure could affect the security of a country national electricity supply. In electrical power networks small oscillations appear from time to time. These oscillations concern the quantities determining the equilibrium point of the system, and following which, system stability and system behaviors are influenced. To improve system behaviors and dynamic stability it is necessary to minimize these transient states. The objective of our study is, first, to check the static stability of the high voltage power to small perturbations of electrical network. In this context, we present a study based on the modal analysis of the linearized system. The results of this analysis allow us to obtain the optimal placement of power regulators PSS injected at the input of voltage regulator AVR based on the matrix of participation. The calculation of these parameters is performed by the regulators method residues. In this paper, the study is structured around one main objective: to have a real interconnection Tunisia-Libya with a stable, efficient and solider operation.

Keywords: Power systems, Optimal control, Modeling and simulation
Abstract: This paper deals with the design and evaluation of a quadratic optimal control method based on bilinear state-space modelling approach in order to improve tha asymptotic stability of Voltage Source Converter (VSC). An steady-state mathematical model of the VSC converter is developed around operating point. VSC converters are increasingly popular with the development of HVDC connection and Multi Terminal DC grid (MTDC). The main role of the studied VSC converter in VSC-HVDC transmission system is to regulate the DC bus voltage. The intention of this paper is to propose a rigorous control method based on optimization algorithms. Finally, the proposed control method is evaluated using Matlab/Simulink.

Keywords: Power systems, Optimization, Optimal control
Abstract: In this paper a new intelligent technique named multi-objective particle swarm optimization (MOPSO) algorithm used to solve profit based unit commitment (PBUCP). The Profit Based Unit Commitment problem is a nonlinear multi-objective optimization problem which involves the simultaneous optimization to maximize the generation companies (GENCOs) profit. The first function is the revenue while the second is the total cost. This optimization involves many constraints such as system power and reserve, unit generation limit, unit minimum ON OFF duration and ramping constraints. The used technique has been tested on IEEE-39 bus system with ten generating units over 24-h time horizon. The simulation results obtained are compared without another technique. The algorithm and simulation are realized with MATLAB 7.4 software.

Keywords: Power systems, Renewable Energy, Modeling and simulation
Abstract: For the purpose of high quality output voltage generation of a stand-alone wind turbine installation, multilevel H-bridge inverter is more suitable then the conventional inverters. This paper presents the modeling and simulation of a stand-alone wind turbine installation feeding a cascade multilevel converter. A performance analysis of the impact of the wind speed variation on the output voltage is carried on. A recommended solution is suggested to avoid this kind of situation.

Keywords: Fault detection and Diagnostics, Networks optimization
Abstract: In their practical applications, Wireless Sensor Networks (WSNs) can experience faults during running. Fur- thermore, faulty data collected in the base station might lead to a wrong judgement.Since the whole system’s performance require the accuracy of data, node fault detection is necessary. Motivated by the requirement of fault detection performance, we propose a distributed fault detection algorithm for wireless senor networks based on Hidden Markov Model (HMM). Firstly, a density of probability method is presented to obtain the possibility of translation of state for each node in the network. Then, a HMM is introduced to characterize the tendency of each node to be faulty. Finally, a distributed fault detection algorithm is proposed based on the HMM. Simulation results show that the proposed HMM-based fault detection achieves high detection accuracy.

Keywords: Fault detection and Diagnostics, Power systems
Abstract: Bayesian model is developed for transformer faults diagnosis using dissolved gas in oil analysis. DGA (Dissolved Gas Analysis) is the traditional and conventional transformer fault diagnosis method, which mainly depends on the experience of operators and of the percentages of dissolved gases. In addition, the only measurement of the gases percentage is not sufficient to evaluate the equipment health. There are several cases where the proportions of dissolved gases remain trapped in the transformer. Regarding this uncertainty and in order to make decisions in a certain environment, the model developed in this study represents a powerful tool for decision making. In addition, one traditional method of dissolved gas analysis does not enable the diagnosis of all faults, for example the Rogers Ratio Method diagnose five faults only, but using the proposed Bayesian network it is possible to diagnose all faults from the same model. To illustrate the advantages of Bayesian methods in transformer fault diagnosis, a study of power station main transformer is conducted and the results are analyzed and discussed

Keywords: Fault detection and Diagnostics, Renewable Energy, Estimations and identification
Abstract: In order to improve reliability of wind turbines, it is important to detect faults as fast as possible.The fault introduced in this work is the dynamics change of the drive train due to the increased friction from its nominal value, will be treated. For diagnosis purpose, a residual generation is used based on a comparison between the nominal generator speed and the observed one obtained by the use of the predictor based LPV subspace identification technique (LPV PBSID)applied at the benchmark system introduced in IFAC SAFEPROCESS 2009 which is modeled as an LPV model considering the wind speed as scheduling variable.

Keywords: Industrial control, Motion control, Power systems
Abstract: This paper presents the synthesis of an adaptive observer which is used for the improvement of the Direct Field Oriented Control (DFOC) of induction motor drives. The observer detects the rotor flux components in the stationary reference frame and the rotor speed using the measure of the stator terminal voltages and currents. The observer is adapted using a simple algorithm which does not imply a high computational load. Stability analysis based on Lyapunov theory is performed in order to guarantee the closed loop stability. Simulation tests under disturbances are provided to evaluate the consistency of the proposed control technique.

Keywords: Fault detection and Diagnostics, Industrial control, Manufacturing systems
Abstract: Defect diagnosis in semiconductor manufacturing is crucial to improve the product quality and to reduce the production cost. When defect is recognized, the objective is to identify which equipment generates it. This paper defines the problem of different types of equipment failures and the impact on the defect diagnosis using the in line control data of the process. A defect diagnosis based on combination of Tool commonality Analysis and Suspected Equipment Confirmation techniques is proposed. Analysis begins by identifying two data horizons: Equipment horizon that specifies the set of suspected equipment and Lot horizon which specifies the inspected samples that are useful for the analysis. A signature table is used to make a binary decision in order to identify the set of suspected equipment and the computing algorithm is described at the end of the paper with an illustration of a numerical example.

Keywords: Fault detection and Diagnostics, Modeling and simulation, Manufacturing systems
Abstract: This communication suggests an extension of an online fault detection method [1] to fault isolation. This proposed method is titled Recursive Principal Component Analysis based on First Order Perturbation RPCA-FOP and it is based on first order perturbation theory (FOP) and partial PCA models where the eigenvalues and eigenvectors of the covariance matrix are updated taking into account the effect of new acquired data as a perturbation.

Keywords: Linear and nonlinear systems, Mathematical systems theory, Autonomous Ssystems
Abstract: This paper includes two main parts: the first part investigates the coexistence and the bifurcation of equilibrium points in the dynamics of permanent magnet sychronous motor (PMSM). Some critical points are detected for a set of system parameters and initial condition, namely Hopf and saddle Node bifurcations. The second part deals with the synchronization of chaos by using a PI regulator. The role of Largest Lyapunov exponents and their computation are among the main issues discussed in this part.

Keywords: Modeling and simulation, Power systems, Renewable Energy
Abstract: It is generally accepted that interleaving techniques are efficient at reducing the input/output ripples and increasing the power output of boost converters operating in the critical conduction mode. Pulse width modulation (PWM) is commonly used to produce the switching pattern. But this technique causes large switching noise peaks at a multiple number of the carrier frequency. This paper proposes Interleaved Boost DC-DC converter suitable for renewable energy applications. The proposed converter utilises a simplified delta-sigma modulation to control the pulse generator. A thorough and effective analysis of the converter is carried out in order to achieve the required system stability and to improve the dynamic performance. The output response characteristics obtained by this method is very much improved compared to the conventional PWM method of control. Simulation results are presented to illustrate the advantages of the proposed scheme. All the advantages of interleaving, such as higher efficiency and reduced ripple for voltage/current, are also maintained in the proposed converter.

Keywords: Motion control, Control algorithms implementation, Modeling and simulation
Abstract: In this work a fixed one step ahead predictive control has been applied to control angular position and linear velocity of an electrical wheelchair. The purpose of such as controller is to assist wheelchair users providing an easier and safer navigation .In addition the importance of this type of control is its effect by operation of the feedforward path to follow in the future, on the other hand, it is possible to exploit fully the information of predefined trajectories, the goal of this strategy is matching the output of the process with setpoint in the future. The study itself was very rewarding because it been conducted since the modeling phase based on Langrage analysis of the wheelchair until the design phase of the control law. The simulation results shows the effectiveness of the one step ahead predictive control in term of reference tracking , where an accurate tracking of angular position and linear velocity modulus smooth reference signals is exhibited.

Keywords: Process control and instrumentation, Fault detection and Diagnostics, Modeling and simulation
Abstract: In this article, a suitable mathematical model of piezoresistive accelerometer was developed and validated by simulation tests. A new relationship was extracted which linked the relative frequency of movement with the natural frequency of piezoresistive accelerometer from the obtained results of simulation. This new formula selects to each frequency range a suitable piezoresistive accelerometer and this good selection of sensor minimizes the resonance effect.

Keywords: Renewable Energy, Power systems, Optimization
Abstract: Hybrid systems of energy production are considered as an interesting alternative for power supply of remote area and non connected sites. Indeed, this paper is focused on the design of an intelligent algorithm and optimized strategy for power management of renewable hybrid system. This system which include wind generator (WG), photovoltaic panel (PV), battery storage (BS) and diesel engine (DE) aims to ensure power supply of an individual isolated house. Indeed, the proposed optimal power management strategy aims to regulate the power flow between the energy sources and the battery storage in order to ensure permanent energy supply of the load. The chosen strategy considers the WG and the PV as the main energy sources and the battery bank as storage system. The DE is considered as an additional source, so it is used like power source emergency. In order to validate the proposed strategy under real conditions; measurements of real weather conditions and power consumption of an individual house are considered. Simulation results are highlighted to demonstrate the feasibility of our proposed approach.

Keywords: Renewable Energy, Control applications, Power systems
Abstract: This paper is presented a silding model control (SMC) based intelligent PID method for a variable speed-constant frequency wind turbine system. This method regards power fluctuation which it is affected by the turbine wind or other factors as disturbance. This controller has two components. Firstly, an intelligent PID controller is designed by estimating the disturbance and compensating them online. Further more, in order to decrease the effect of error estimation, an extra sliding model controller is designed for compensating it. This method has been tested by a 5MW wind turbine system by Matlab/Simulink platform. The results confirm that the proposed method is powerful for the reactive power and is superior in the respond time.

Keywords: Renewable Energy, Industrial control
Abstract: Lately, fractional PIλDμ controller has gained more interests because it involves two more tuning parameters, the fractional order integration λ and the fractional order differentiation , in their structure. This type of controller has been introduced in the control system theory in a continuous effort to enhance the system control quality performances. In this paper a self-tuning fractional PIλDμ controller for wind turbine speed control is proposed. The fractional PIλDμ controller’s five parameters are self-tuned as the system dynamics or operating points change using formulas based on a desired closed loop response. A simulation study of the wind turbine speed control has been done to demonstrate and validate the performance and effectiveness of the proposed control scheme.

Keywords: Renewable Energy, Modeling and simulation, Modeling of complex systems
Abstract: High electrical power efficiency is desired characteristic in high performance solar cells. In this paper we present an analytical investigation SiGe solar cell including texture morphology effects, in order to study the impact of the texture morphology on the electrical performances. Based on 2-D analytical investigation of SiGe single-junction (SiGe(n)/Si(p)) thin film solar cell, in the present paper new analytical models of optical and electrical parameters are developed to investigate the impact of the surface texture morphology on the enhancement of the solar cell optical and electrical behaviors for high performance applications. In this context, electrical characteristics of the investigated design are analyzed and compared with conventional SiGe solar cell, without surface texture morphology

Keywords: Renewable Energy, Modeling and simulation, Modeling of complex systems
Abstract: This paper presents a new amorphous triple-junction thin-film SiGe solar cell design enhancing the power efficiency for high performance photovoltaic applications. To do that, a new approach based on multi-trench technique to improve the electrical performance, which are the electrical efficiency and fill factor, is presented and discussed. The key idea behind this contribution is to introduce new multi-trench region in the intrinsic layer of the top sub-cell, in order to modulate the electrical behavior, total resistance, of the triple-junction solar cell. The numerical calculations demonstrate that, according to the trench size effects on both series resistance and shunt resistance, the fill factor and electrical efficiency values are strongly related to the number and structure of the trenches. To justify the validity of our design suitable for implementation in photovoltaic system and solar cell simulators, the obtained results are compared with the available research data and they shows a satisfactory improvement, consequently, demonstrating the efficiency of our design.

Keywords: Renewable Energy, Power systems, Control applications
Abstract: this paper deals with advanced supervisor control for a hybrid generation system. Such system works in island mode and comprises a photovoltaic panel and a battery/super capacitor energy storage system. The principal aims of the proposed supervisor are, firstly, to control the energy flow of the system in order to satisfy the load power demand, secondly, to manage the loads according to the power availability to preserve the battery state of charge and to prevent the system failure under any condition. The performance of the proposed control strategy are tested by simulation in different operating situation. The simulation result shows the efficiency of the proposed control strategy, as it improves the energy balance of the system and increases its reliability.