Search

This paper presents an artificial neural network-based adaptive control approach for a doubly-fed induction generator (DFIG) based wind energy conversion system (WECS). The control objectives are: (1) extraction of maximum available power from the wind; (2) stator reactive power regulation according to the grid requirements. Artificial neural networks are used to estimate some nonlinear functions which represent the system uncertainties. The Lyapunov method is employed to prove the asymptotic stability of the closed-loop system. Numerical simulation results illustrate the effectiveness of the proposed control scheme in comparison with both vector control and sliding mode control techniques.

This paper studies the design of neuro- adaptive tracking control schemes for non-integer order non-square systems subject to time-varying output constraints and input nonlinearities . It should first be stated that by employing the mean-value theorem, the original non-affine non-square system with actuator nonlinearities is converted into an equivalent affine square form. Neural networks , Barrier Lyapunov Functions and Nussbaum functions are then incorporated to overcome the difficulties raised by the uncertain nonlinear dynamics, output constraints and unknown control directions, respectively. In a further step, in order to systematically derive the control signals and updating laws, the Backstepping technique is applied. It is shown that by using the proposed adaptive controller , the semi-global asymptotic tracking and the boundedness of all variables in the closed-loop system are guaranteed without transgression of the constraints. The foremost contributions of this paper include: (1) by means of new lemmas and corollaries based on Caputo fractional derivative definitions, techniques and approaches related to the stability analysis and controllability of integer-order plants are extended to fractional-order non-square ones, and (2) the ‘explosion of complexity’ issue is fixed. Finally, simulation results are provided to reveal the effectiveness of the proposed control scheme.

In this paper an optimal fuzzy sliding mode control (FSMC) strategy is introduced for doubly fed induction generator-based wind turbine (DFIG-based WT). The control objective is to ensure power extraction maximization and null stator reactive power regulation according to the grid requirements. To this end, the sliding mode control (SMC) technique is combined with a simple fuzzy inference system to avoid the undesirable chattering phenomenon inherent to the conventional SMC. The proposed FSMC strategy is derived using the Lyapunov approach to guarantee the closed loop system’s stability. To obtain optimal control performances, the membership function parameters of the incorporated fuzzy system are tuned using an improved population-based optimization algorithm, which consists on the combination of particle swarm optimization (PSO) and gravitational search algorithm (GSA). Finally, the performances of the proposed control scheme, called PSO–GSA based FSMC are evaluated in comparison with PSO based FSMC and GSA based FSMC systems.

A new LMI design technique is developed to address the problem of circle criterion-based $\mathcal{H}_{\infty}$ observer design for nonlinear systems. The developed technique applies to both locally Lipschitz as well as monotonic nonlinear systems, and allows for nonlinear functions in both the process dynamics and output equations. The LMI design condition obtained is less conservative than all previous results proposed in the literature for these classes of nonlinear systems. By judicious use of a modified Young’s relation, additional degrees of freedom are included in the observer design. These additional decision variables enable improvements in the feasibility of the obtained LMI. Several recent results in the literature are shown to be particular cases of the more general observer design methodology developed in this paper. Illustrative examples are given to show the effectiveness of the proposed methodology. The application of the method to slip angle estimation in automotive applications is discussed and experimental results are presented.

© 1967-2012 IEEE. This paper proposes and experimentally validates a two-stage approach for coupled lateral vehicle state and tire model estimation. In a first stage, an extended Kalman filter is employed which provides vehicle slip angles and lateral tire forces from commercial low-cost vehicle sensors. The obtained estimates are exploited in the second stage, where a (quasi-static) tire model is fitted to this data. A major issue in this estimation process is the typical instability of these estimators for situations with (prolonged) straight driving. This issue is traced back to a lack of local observability. The use of a variable model covariance is introduced as a practical method to obtain a stable estimator, irrespective of the unobservability. The developed methodology has a low computational load and the Kalman estimator is able to run in real time, whereas the tire model parameter fitting is cheap enough to run online. The proposed methodology is validated experimentally and provides reliable results in variable driving conditions. ispartof: IEEE Transactions on Vehicular Technology vol:66 issue:11 pages:9727-9742 status: published

This research is concerned with the problem of generalized function projective synchronization of nonlinear uncertain time-delay incommensurate fractional-order chaotic systems with input nonlinearities. The considered problem is challenging owing to the presence of unmeasured master-slave system states, external dynamical disturbances, unknown nonlinear system functions, unknown time-varying delays, quantized outputs, unknown control directions unknown actuator nonlinearities (backlash-like hysteresis, dead-zone and asymmetric saturation actuators) and distinct fractional-orders. Under some mild assumptions and using Caputo's definitions for fractional-order integrals and derivatives, the design procedure of the proposed neural adaptive controller consists of a number of steps to solve the generalized function projective synchronization problem. First, smooth functions and the mean value theorem are utilized to overcome the difficulties from actuator nonlinearities and distributed time-varying delays, respectively. Then, a simple linear observer is established to estimate the unknown synchronization error variables. In addition, a Nussbaum function is incorporated to cope with the unknown control direction and a neural network is adopted to tackle the unknown nonlinear functions. The combination of the frequency distributed model, the Razumikhin Lemma, the neural network parameterization, the Lyapunov method and the Barbalat's lemma is employed to perform the stability proof of the closed-loop system and to derive the adaption laws. The major advantages of this research are that: (1) the Strictly Positive Real (SPR) condition on the estimation error dynamics is not required, (2) the considered class of master-slave systems is relatively large, (3) all signals in the resulting closed-loop systems are semi-globally uniformly ultimately bounded and the synchronization errors semi-globally converge to zero. Finally, numerical examples are presented to illustrate the performance of the proposed synchronization scheme.

This paper solves the problem of projective lag-synchronization based on output-feedback control for chaotic drive-response systems with input dead-zone and sector nonlinearities. This class of the drive-response systems is assumed in Brunovsky form but with unavailable states and unknown dynamics. To effectively deal with both dead-zone and sector nonlinearities, the proposed controller is designed in a variable-structure framework. To online learn the uncertain dynamics, adaptive fuzzy systems are used. And to estimate the unavailable states, a simple synchronization error is constructed. To prove the stability of the overall closed-loop system (controller, observer, and drive-response system) and to design the adaptation laws, a Lyapunov theory and strictly positive real (SPR) approach are exploited. Finally, three academic examples are given to show the effectiveness of this proposed lag-synchronization scheme.

Although extensive research has been conducted to design path-following algorithms for automated vehicles, the cross comparison between different path-following controllers is still weakly-analyzed. Therefore, we benchmarked five path-following algorithms to evaluate their performance according to various disturbances like gust wind, drop of road friction coefficient and inaccurate GPS localization. The comparison was carried out in simulation environment between geometrical-based, path controller with preview, LQR, linear MPC and observer-based controller with integral action approaches.

This paper deals with the active fault tolerant control (AFTC) problem for a class of multiple-input multiple-output (MIMO) uncertain nonlinear systems subject to sensor faults and external disturbances. The proposed AFTC method can tolerate three additive (bias, drift and loss of accuracy) and one multiplicative (loss of effectiveness) sensor faults. By employing backstepping technique, a novel adaptive backstepping-based AFTC scheme is developed using the fact that sensor faults and system uncertainties (including external disturbances and unexpected nonlinear functions caused by sensor faults) can be on-line estimated and compensated via robust adaptive schemes. The stability analysis of the closed-loop system is rigorously proven using a Lyapunov approach. The effectiveness of the proposed controller is illustrated by two simulation examples.

This research fixed as objective the study and the analysis of buildings belonging to the colonial period. This buildings important damages today, whether it is by the custom or under the influence of time. So and considering their importances in the national history and their values of architectural heritage; we attempted to develop a method of analysis susceptible to help in their long-lasting identification. The area of this study was the city center of Annaba, which reflects a typology recognized through the majority of the Algerian big cities. The developed approach consists in making a detailed reading of the various architectural and architectonic elements composing the colonial facade. The end, we were able to identify the basic typologies, which can serve as references for the composition of a facade of the XIXth and XXth century to Annaba. Beyond this receipt, our work could be of use to future operations of rehabilitation, renovation, and requalification or of protection of this type of construction. Also this architecture would inspire contemporary realizations.

A l’instar des villes Algériennes, après la dissolution de sa Régie Municipale RMCA, la ville d’Annaba, n’a pas échappé aux effets négatifs générés par la libéralisation du secteur de transport impulsé par la loi n° 88-17 du 10 mai 1988 portant orientation et organisation des transports terrestres, et dont ses effets qualifiables de «stigmates» demeurent à ce jour.Cet article se penche sur l’opération de libéralisation ordonnée par l’état pendant le début des Années 90, en proposant un phasage chronologique relatif à son évolution, tout en mettant la lumière sur ses effets les plus manifestes à l’échelle nationale et surtout sur le plan urbain par rapport au périmètre de transport de la ville d’Annaba, ceci à travers ses différents volets organisationnels et fonctionnels.Mots clés: Libéralisation - Transport public - Chronologie - Urbain - OrganisationEnglish Title: Liberalization as a source of deregulation of public transport in Annaba cityEnglish AbstractSimilarly at almost of the Algerian cities, after the dissolution of the Municipal Board RMCA, the city of Annaba doesn’t escape from the negative effects generated by the liberalization of the transport sector; Promoted by Law 88-17 of May 10th,1988, concerning the orientation and organization of land transportation, including its effects classifiable “stigmata”, who persists until the present .This work examines the orderly liberalization process by the state during the early 90's, offering a chronology of its evolution, while shedding light on its most obvious effects at different levels, nationally and especially in urban scale compared to PUT perimeter of urban transport of Annaba city, also through its various organizational and functional aspects.Keywords: Liberalization - Public transport - Chronology - Urban - Organization

Cet article analyse les politiques patrimoniales mises en place par l’état algérien pour la préservation du patrimoine architectural en général et celui hérité de l’époque coloniale française en particulier ; et souligne l’important arsenal juridique renforcé depuis 1998.Nous tenterons à travers l’exemple de l’hôtel de ville d’Annaba, de mettre en exergue les spécificités des politiques patrimoniales et des opérations de réhabilitation du patrimoine architectural datant de l’époque coloniale française, afin d’identifier les rapports entre le jeu des acteurs locaux, les logiques opérationnelles de prise en charge de ce patrimoine, et de cerner les niveaux de défaillances dans la chaine de prise de décision et leurs impacts sur le niveau de dégradation et de méconnaissance de ce legs.Mots clés: patrimoine architectural- hôtel de ville – réglementation - réhabilitationEnglish Title: The architectural heritage of the French colonial era to the prism of Algerian patrimonial policies: case of the town hall of BôneEnglish AbstractThis article analyzes the patrimonial policies implemented by the Algerian state for the preservation of architectural heritage in general and that inherited from the French colonial period in particular; and high lights the important legal arsenal reinforced since 1998.We will try through the example of the city of Annaba Hotel, to highlight the specificities of heritage policies and rehabilitation operations of the architectural heritage dating from the French colonial era, in order to identify the relationship between the set of local actors, the operational logic of management of that heritage, and to identify the levels of failures in the chain of decision-making and their impact on the level of degradation and ignorance of this legacy.Keywords: architectural heritage - city hall – actors – regulation - rehabilitation

This work aims toevaluate the reduce pollutant emission by steel reheating furnaces andoperating process of the diffusion flame industrials burners. The exampledeveloped here is particularly interested in the influence of the airpreheating temperature on NOx emissions as well as the dynamic characteristicsand heat flow. The study was conducted on an industrial gas burners 250 kilowatt.Numerical simulations are per formed using the computer code FLUENT, using theturbulence standard k-ε model coupled to turbulent combustion ED (EddyDissipation).The probability density function PDF model (6 species andreactions 3) with a chemical equilibrium model. The results obtained fordifferent air preheat temperatures show that NOx emissions depend on the airpreheat temperature.

This paper presents a new approach that avoids the over-fitting and complexity problems suffered in the construction of decision trees. Decision trees are an efficient means of building classification models, especially in industrial engineering. In their construction phase, the two main problems are choosing suitable attributes and database components. In the present work, a combination of attribute selection and data sampling is used to overcome these problems. To validate the proposed approach, several experiments are performed on 10 benchmark datasets, and the results are compared with those from classical approaches. Finally, we present an efficient application of the proposed approach in the construction of non-complex decision rules for fault diagnosis problems in rotating machines.

This article aims to introduce a projective synchronization approach based on adaptive fuzzy control for a class of perturbed uncertain multivariable nonaffine chaotic systems. The fuzzy-logic systems are employed to approximate online the uncertain functions. A Lyapunov approach is used to design the parameter adaptation laws and to demonstrate the boundedness of all signals of the closed-loop system as well as the convergence of the synchronization errors to bounded residual sets. Finally, numerical simulation results are presented to verify the feasibility and effectiveness of the proposed synchronization system based on fuzzy adaptive controller. © 2014 Wiley Periodicals, Inc. Complexity 21: 180-192, 2015

In this paper, a sensorless adaptive neuro-fuzzy backstepping control scheme is developed for induction machines with unknown model, uncertain load-torque and nonlinear friction where the speed is obtained using the model reference adaptive system (MRAS). Neurofuzzy systems are used to online approximate the uncertain nonlinearities and an adaptive backstepping technique is employed to systematically construct the control law. The MRAS observer is based on two different models, one that is speed independent (reference model) and another that is speed dependent (adjustable model). The speed is estimated via the outputs of the two models. The proposed sensorless controller guarantees the tracking errors converge to a small neighbourhood of the origin and the boundedness of all closed-loop signals what demonstrate the effectiveness of the proposed approach.

This paper is concerned with actuator fault detection in nonlinear systems in the presence of disturbances. A nonlinear unknown input observer is designed and the output estimation error is used as a residual for fault detection. To deal with the problem of high Lipschitz constants, a modified mean-value theorem is used to express the nonlinear error dynamics as a convex combination of known matrices with time-varying coefficients. Moreover, the disturbance attenuation is performed using a modified H∞ criterion. A sufficient condition for the existence of an unknown input observer is obtained using a linear matrix inequality formula, and the observer gains are obtained by solving the corresponding set of inequalities. The advantages of the proposed method are that no a priori assumption on the unknown input is required and that it can be applied to a large class of nonlinear systems. Performances of the proposed approach are shown through the application to a diesel engine model.

The dynamic process of the interaction between a turbulent jet methane diffusion flame and a lateral wall was experimentally studied. The evolution of the flame temperature field with the Nitrogen dilution of the methane jet flame was studied for 0.2N2, 0.4N2, 0.6N2, 0.8N2, the interaction between the diffusion flame and the lateral wall is characterized for different distance between the wall and the central axis of the jet flame, the dilution is found to play the central role in the flame extinction process. The flame response as the lateral wall approaches from infinity and the increasing of the dilution rate make the flame extinction more rapidly than the flame without dilution, when the nitrogen dilution rate increase the flame temperature decrease.

A fuzzy approximation-based indirect adaptive control is investigated for a class of unknown non-affine non-linear systems with unknown control direction. An equivalent model in affine-like form is first derived for the original non-affine system by using a Taylor series expansion. Next, a fuzzy indirect adaptive control is designed based on this affine-like equivalent model. In this control scheme, the adaptive fuzzy systems are used to appropriately approximate the equivalent affine model’s unknown non-linearities, whereas the Nussbaum gain function is used to deal with the unknown control directions (being closely related to the sign of control gain matrix). A decomposition property of the control gain matrix is fully exploited in the controller design and the stability analysis. It is proven that, under some appropriate assumptions, the proposed control scheme can achieve that all the signals in the closed-loop control system are bounded and the tracking errors converge to a small neighbourhood around zero. Effectiveness of the developed scheme is illustrated by two simulation examples.

International audience; A complex based on bis-pyrazolyl N-tripodal ligand known to present a good catalytic activity for the oxidation of 3,5-di-tert-butylcatechol is used to prepare a novel biomimetic sensor for the determination of catechol derivatives. The modified electrode prepared by encapsulation of the complex in a Nafion® film leads to an electrochemical signal 4.4 times higher than with a glassy carbon electrode for dopamine detection in pH 7 medium. After optimization of the conditions used to immobilize the catalyst on the electrode surface, a calibration curve was obtained with linearity in the range of 30–320 μmol L−1 and a detection limit of 8 μmol L−1. The sensor was not affected by ascorbic acid and uric acid in similar concentrations to dopamine and its electrochemical response was stable after 40 determinations. The biomimetic sensor can also be used for the detection of other catechol derivatives.

International audience; 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.

In this paper, a projective synchronization problem of master-slave chaotic systems is investigated. More specifically, a fuzzy adaptive slave chaotic system subject to both sector nonlinearities and dead-zone in the input channel is proposed using only the measurable output of the master system thanks to a suitable observer. The asymptotical projective synchronization between the master and slave systems is achieved by an adequate fuzzy adaptive variable-structure control system. The underlying parameter adaptation design as well as the asymptotical synchronization and stability analysis are carried out using a Lyapunov based approach. The distinctive feature of the control design is that the uncertainties function and the gain reduction tolerances of the dead-zone are no longer required to be known thanks to the parameter adaptation capability of the control system. The proposed synchronization scheme is extended to two classes of the master-slave chaotic systems with time-delays. By using the Lyapunov-Krasovskii approach, some stability conditions relating to these classes are derived. Simulation results are given to show the effectiveness of the proposed projective synchronization scheme.

International audience; This paper investigates fuzzy adaptive control schemes for a class of multi-input multi-output (MIMO) unknown nonlinear systems with known and unknown sign of the control gain matrix.Three fuzzy adaptive control schemes are developed. In the design of the second and third controller, we will exploit a decomposition of the control gain matrix into a symmetric positive-definite matrix, a diagonal matrix with diagonal entries +1 or −1 and a unity upper triangular matrix. The Nussbaum-type function is used to deal with the unknown control direction (i.e. the unknown sign of the control gain matrix). For updating the parameters of the fuzzy system, an adaptation proportional-integral (PI) law is proposed. Theoretical results are illustrated through two simulation examples.

This work announces an eleven-term novel 4-D hyperchaotic system with two quadratic nonlinearities. A qualitative analysis of the properties of the novel 4-D hyperchaotic system is presented. A special feature of our novel hyperchaotic system is that it has three equilibrium points of which two are unstable and one is locally asymptotically stable. The Lyapunov exponents of the novel hyperchaotic system are obtained as L1 = 1.5146, L2 = 0.2527, L3 = 0 and L4 = -12.7626. The Kaplan-Yorke dimension of the novel hyperchaotic system is derived as DKY. = 3.1385. Next, this work describes the design of an adaptive controller for the global hyperchaos synchronisation of identical novel hyperchaotic systems with unknown parameters. MATLAB simulations are shown to describe all the main results derived in this work.

In this paper, a new adaptive iterative learning control scheme is proposed to deal with nonlinearly parameterised strict feedback systems under alignment condition in the presence of input saturation constraint. The learning controller is designed by using the command filtered adaptive backstepping design procedure. The nonlinearly connected parameters are separated from the local Lipschitz continuous nonlinear functions and then learning laws are designed in iteration domain. To overcome the problem of input saturation, an auxiliary system is constructed with the same order as that of the systems under consideration. It is proved that the proposed control scheme can guarantee that all signals of the resulting closed-loop system remain bounded, and the tracking error converges to zero as the iteration number goes to infinity. A simulation example is included to illustrate the effectiveness of the proposed scheme.