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In this paper, the applications of artificial intelligence-based methods for tracking the maximum power point have been reviewed and analysed. The reviewed methods are based upon neural networks, fuzzy logic, evolutionary algorithms, which include genetic algorithms, particle swarm optimization, ant colony optimization, and other hybrid methods. Rapid advances in programmable logic devices (PLDs) including field programmable gate arrays (FPGAs) give good opportunities to integrate efficiently such techniques for real time applications. An attempt is made to highlight the future trends and challenges in the development of embedded intelligent digital maximum power point tracking (MPPT) controllers into FPGA chip. Special attention is also given to the cost, complexity of implementation, efficiency, and possible practical realization. We believe that this review provides valuable information for engineers, designers and scientist working in this area and show future trends in the development of embedded intelligent techniques for renewable energy systems. © 2014 Elsevier Ltd.

Mellit A.,Jijel University | Kalogirou S.A.,Cyprus University of Technology
Renewable Energy | Year: 2011

Due to the various seasonal, monthly and daily changes in meteorological data, it is relatively difficult to find a suitable model for Photovoltaic power supply (PVPS) system. This paper deals with the modelling and simulation of a PVPS system using an Adaptive Neuro-Fuzzy Inference Scheme (ANFIS) and the proposition of a new expert configuration PVPS system. For the modelling of the PVPS system, it is required to find suitable models for its different components (ANFIS PV generator, ANFIS battery and ANFIS regulator) that could give satisfactory results under variable climatic conditions in order to test its performance and reliability. A database of measured climate data (global radiation, temperature and humidity) and electrical data (photovoltaic, battery and regulator voltage and current) of a PVPS system installed in Tahifet (south of Algeria) has been recorded for the period from 1992 to 1997. These data have been used for the modelling and simulation of the PVPS system. The results indicated that the reliability and the accuracy of the simulated system are excellent and the correlation coefficient between measured values and those estimated by the ANFIS gave a good prediction accuracy of 98%. Additionally, test results show that the ANFIS performed better than the Artificial Neural Network (ANN), which has also being tried to model the system. In addition, a new configuration of an expert PVPS system is proposed in this work. The predicted electrical data by the ANFIS model can be used for several applications in PV systems. © 2010 Elsevier Ltd.

Boulkroune A.,Jijel University | Msaad M.,National Engineering School of Caen
Fuzzy Sets and Systems | Year: 2012

In this paper, an observer-based fuzzy adaptive controller for nonlinear systems with unknown control gain sign is investigated. Because the system states are not available for measurement, a tracking-error observer is constructed. In this controller, the adaptive fuzzy system is used to approximate the unknown nonlinearities and the Nussbaum function is incorporated to deal with the unknown control direction (i.e. with the unknown control gain sign). The stability of the closed-loop system is proven using the strictly positive real (SPR) condition and Lyapunov theory. Finally, simulation results are given to verify the feasibility and effectiveness of the proposed controller. © 2011 Elsevier B.V. All rights reserved.

Ahriche A.,Jijel University | Nasri S.,United Arab Emirates University
Physical Review D - Particles, Fields, Gravitation and Cosmology | Year: 2012

We propose a minimal extension of the standard model by two real singlet fields that could provide a good candidate for light dark matter, and give a strong first order electroweak phase transition. As a result, there are two CP even scalars: one is lighter than ∼70GeV, and the other one with mass in the range ∼280-400GeV, and consistent with electroweak precision tests. We show that the light scalar mass can be as small as 25 GeV while still being consistent with the LEP data. The predicted dark matter scattering cross-section is large enough to accommodate CoGeNT and can be probed by future XENON experiment. We also show that for dark matter mass around 2 GeV, the branching fraction of the process (B +→K ++2(DM)) can be accessible in SuperB factories. © 2012 American Physical Society.

Touafek N.,Jijel University | Elsayed E.M.,King Abdulaziz University
Mathematical and Computer Modelling | Year: 2012

In this paper we deal with the periodic nature and the form of the solutions of the following systems of rational difference equations xn+1=xn-3±1±xn-3yn-1,yn+1=yn-3±1±yn-3xn-1 with a nonzero real number's initial conditions. © 2011 Elsevier Ltd.

Haouat S.,Jijel University
Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics | Year: 2014

In this work we have studied the consequences of the minimal length, which arises in many theories of quantum gravity, on the Scattering of a point particle by a spherically symmetric potential. The modified Schrödinger equation is factorized to be of second order in position space representation. For the square well potential analytic expressions for the scattering states are obtained. Then the phase shifts are deduced. It is shown that the minimal length has two effects on the resonant scattering. The first one is that the minimal length increases slightly the resonant cross section and the second is the shift of the position of the resonances. © 2013 The Author.

Bouaziz D.,Jijel University
Annals of Physics | Year: 2015

The Kratzer's potential V(r)=g1/r2-g2/r is studied in quantum mechanics with a generalized uncertainty principle, which includes a minimal length (δX)min=h{stroke}5β. In momentum representation, the Schrödinger equation is a generalized Heun's differential equation, which reduces to a hypergeometric and to a Heun's equations in special cases. We explicitly show that the presence of this finite length regularizes the potential in the range of the coupling constant g1 where the corresponding Hamiltonian is not self-adjoint. In coordinate space, we perturbatively derive an analytical expression for the bound states spectrum in the first order of the deformation parameter β. We qualitatively discuss the effect of the minimal length on the vibration-rotation energy levels of diatomic molecules, through the Kratzer interaction. By comparison with an experimental result of the hydrogen molecule, an upper bound for the minimal length is found to be of about 0.01 Å. We argue that the minimal length would have some physical importance in studying the spectra of such systems. © 2015 Elsevier Inc.

Beicha A.,Jijel University
Journal of Power Sources | Year: 2012

This paper presents an electrochemical model for simulation and evaluation of the performance of proton exchange membrane (PEM) fuel cell. The results of the model are used to predict the efficiency and power of the fuel cell as a function of operational parameters of the cell, like temperature, partial pressures and membrane humidity. The influence of temperature on fuel cell's characteristics is more pronounced than the influence of partial pressures and membrane humidity. The effect of platinum loading on cell performance is examined with Pt loadings of 0.18, 0.38 and 0.4 mg cm -2. The kinetic parameters (electron transfer coefficient, exchange current density) are found to be platinum loading dependent. © 2012 Elsevier B.V. All rights reserved.

Summary This paper deals with iterative learning control (ILC) design to solve the trajectory tracking problem for rigid robot manipulators subject to external disturbances, and performing repetitive tasks. A D-type IlC is presented with an initial condition algorithm, which gives the initial state value in each iteration automatically. Thus, the resetting condition (the initial state error is equal to zero) is not required. The λ-norm is adopted as the topological measure in our proof of the asymptotic stability of this control scheme, over the whole finite time-interval, when the iteration number tends to infinity. Simulation results are presented to illustrate the effectiveness of the proposed control scheme. © Cambridge University Press 2011.

Mellit A.,Jijel University
Advances in Engineering Software | Year: 2010

Recent advances in artificial intelligence techniques have allowed the application of such technologies in real engineering problems. In this paper, an artificial neural network-based genetic algorithm (ANN-GA) model was developed for generating the sizing curve of stand-alone photovoltaic (SAPV) systems. Due to the high computing time needed for generating the sizing curves and complex architecture of the neural networks, the genetic algorithm is used in order to find the optimal architecture of the ANN (number of hidden layers and the number of neurons within each hidden layer). Firstly, a numerical method is used for generating the sizing curves for different loss of load probability (LLP) corresponding to 40 sites located in Algeria. The inputs of ANN-GA are the geographical coordinates and the LLP while the output is the sizing curve represented by CA = f(CS) (i.e., 30-points were taken from each sizing curve). Subsequently, the proposed ANN-GA model has been trained by using a set of 36 sites, whereas data for 4 sites (randomly selected) which are not included in the training dataset have been used for testing the ANN-GA model. The results obtained are compared and tested with those of the numerical method in order to show the effectiveness of the proposed approach. © 2009 Elsevier Ltd. All rights reserved.

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