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Alkhoury Z.,CNRS Laboratory of Computer Science and Automatic Control Systems | Alkhoury Z.,Lille University of Science and Technology | Petreczky M.,CNRS Lille Research Center in Informatics, Signal and Automatic control | Mercere G.,CNRS Laboratory of Computer Science and Automatic Control Systems
Automatica | Year: 2017

In this paper, the identifiability of discrete-time Affine Linear Parameter-Varying (ALPV) models is studied. Examples are presented to show that, in general, the identifiability of ALPV model parameterizations does not guarantee the identifiability of the LTI parameterizations composed of frozen LTI models. A new sufficient and necessary condition is then introduced in order to guarantee the structural identifiability for ALPV parameterizations. The identifiability of this class of parameterizations is related to the lack of state–space isomorphisms between any two models corresponding to different parameter values. In addition, we present a sufficient and necessary condition for local structural identifiability, and a sufficient condition for (global) structural identifiability which are both based on the rank of a user-defined matrix. These latter conditions allow systematic verification of identifiability. Numerical examples are finally presented to illustrate our results. © 2017 Elsevier Ltd


Koulougli D.,LARI | Hadjali A.,CNRS Laboratory of Computer Science and Automatic Control Systems | Rassoul I.,Mouloud Mammeri University
Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS | Year: 2017

Crowdsourcing is defined as an emerging computation paradigm, where the power of crowds is utilized to facilitate large scale tasks that are costly or time consuming with traditional methods. One of the most important technical challenges of crowdsourcing is quality control of workers' responses. Human factors play a key role in achieving high quality answers in crowdsourcing-based solving tasks. The most major factor is pertained to the uncertainty of workers about the responses that they provide to resolve the task at hand. On the other hand, workers may have diverse levels of expertise and skill. It is then important to take into account both the degrees of uncertainty and expertise to return the most correct reliable answer. In this paper, we propose a belief functions-based approach to achieve this goal. We conduct also some comprehensive experiments to validate the effectiveness of our proposal. © 2016 IEEE.


Vayssettes J.,Higher Institute of Aeronautics and Space | Mercere G.,CNRS Laboratory of Computer Science and Automatic Control Systems | Prot O.,University of Limoges
Automatica | Year: 2016

This article aims at giving a new answer for the challenging problem of the parametrisation of multi-input multi-output matrix fraction descriptions. In order to reach this goal, new parametrisations of matrix fraction descriptions, called fully-parametrised left matrix fraction descriptions (F-LMFD), are first introduced. Their structural properties as well as their suitability for multi-input multi-output model description are more precisely analysed. As any over-parametrised model description, the F-LMFD cannot describe a transfer function uniquely. The structure of the space of equivalent F-LMFD is then investigated through the determination of its basis. The study carried out in this article is the prelude to a computational improvement of the identification of matrix fraction descriptions with gradient-based optimisation methods. © 2016 Elsevier Ltd. All rights reserved.


Mercere G.,CNRS Laboratory of Computer Science and Automatic Control Systems | Prot O.,University of Limoges | Ramos J.A.,Nova Southeastern University
IEEE Transactions on Automatic Control | Year: 2014

While determining the order as well as the matrices of a black-box linear state-space model is now an easy problem to solve, it is well-known that the estimated (fully parameterized) state-space matrices are unique modulo a non-singular similarity transformation matrix. This could have serious consequences if the system being identified is a real physical system. Indeed, if the true model contains physical parameters, then the identified system could no longer have the physical parameters in a form that can be extracted easily. By assuming that the system has been identified consistently in a fully parameterized form, the question addressed in this paper then is how to recover the physical parameters from this initially estimated black-box form. Two solutions to solve such a parameterization problem are more precisely introduced. First, a solution based on a null-space-based reformulation of a set of equations arising from the aforementioned similarity transformation problem is considered. Second, an algorithm dedicated to nonsmooth optimization is presented to transform the initial fully parameterized model into the structured state-space parameterization of the system to be identified. A specific constraint on the similarity transformation between both system representations is added to avoid singularity. By assuming that the physical state-space form is identifiable and the initial fully parameterized model is consistent, it is proved that the global solutions of these two optimization problems are unique. The proposed algorithms are presented, along with an example of a physical system. © 2014 IEEE.


Petreczky M.,University of Lille Nord de France | Petreczky M.,Ecole Des Mines de Douai | Mercere G.,CNRS Laboratory of Computer Science and Automatic Control Systems
Proceedings of the IEEE Conference on Decision and Control | Year: 2012

We formulate a Kalman-style realization theory for discrete-time affine LPV systems. We characterize those input-output behaviors which exactly correspond to affine LPV systems. In addition, we present necessary and sufficient conditions for minimality of affine LPV systems and show that equivalent minimal realizations are unique up to isomorphism. The results are derived by reducing the problem to the realization problem for linear switched systems. In addition, we show that an input-output map has a realization by an affine LPV system if and only if it satisfies certain types of input-output equations. © 2012 IEEE.


Bellatreche L.,CNRS Laboratory of Computer Science and Automatic Control Systems | Khouri S.,CNRS Laboratory of Computer Science and Automatic Control Systems | Khouri S.,National School in Computer Science | Berkani N.,National School in Computer Science
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

In last decades, semantic databases (SDB) emerge and become operational databases, since the major vendors provide semantic supports in their products. This is mainly due to the spectacular development of ontologies in several domains like E-commerce, Engineering, Medicine, etc. Contrary to a traditional database, where its tuples are stored in a relational (table) layout, a SDB stores independently ontology and its instances in one of the three main storage layouts (horizontal, vertical, binary). Based on this situation, SDB become serious candidates for business intelligence projects built around the Data Warehouse (DW) technology. The important steps of the DW development life-cycle (user requirement analysis, conceptual design, logical design, ETL, physical design) are usually dealt in isolation way. This is mainly due to the complexity of each phase. Actually, the DW technology is quite mature for the traditional data sources. As a consequence, leveraging its steps to deal with semantic DW becomes a necessity. In this paper, we propose a methodology covering the most important steps of life-cycle of semantic DW. Firstly, a mathematical formalization of ontologies, SDB and semantic DW is given. User requirements are expressed on the ontological level by the means of the goal oriented paradigm. Secondly, the ETL process is expressed on the ontological level, independently of any implementation constraint. Thirdly, different deployment solutions according to the storage layouts are proposed and implemented using the data access object design patterns. Finally, a prototype validating our proposal using the Lehigh University Benchmark ontology is given. © Springer-Verlag 2013.


Vayssettes J.,Higher Institute of Aeronautics and Space | Mercere G.,CNRS Laboratory of Computer Science and Automatic Control Systems
Proceedings of the IEEE Conference on Decision and Control | Year: 2014

A new parametrisation of matrix fraction descriptions, named fully-parametrised left matrix fraction description (F-LMFD) is introduced in this article. This one contains ny2 over-parameters and consequently does not uniquely define a transfer function. Based on a study of the spanned equivalence class, local parametrisations of F-LMFD are then proposed to reduce the search space dimension when a gradient-based optimisation is performed. The formulation of the Gauss-Newton method is then considered and the new convergence scheme based on these local parametrisations is given. This one has a better numerical conditioning and is shown to avoid the numerical locking that can occurs with the conventional convergence schemes, based on minimal parametrisations of LMFD. The improvement of the convergence of the Gauss-Newton method is illustrated with the identification of a shaker. © 2014 IEEE.


Vizer D.,Budapest University of Technology and Economics | Mercere G.,CNRS Laboratory of Computer Science and Automatic Control Systems
Periodica Polytechnica, Electrical Engineering | Year: 2014

When the identification of linear parameter-varying (LPV) models from local experiments is considered, the question of the necessary number of local operating points as well as the problem of the efficient interpolation of the locally-estimated linear time-invariant models arise. These challenging problems are tackled herein by using the H∞-norm. First, thanks to the nu-gap metric, an heuristic technique is introduced to optimize the number as well as the position of the local operating points (along a given trajectory of the scheduling variables) with respect to the information brought by the local models. Having access to a reliable set of local models, the second step of the procedure, i.e., the parameter estimation step, consists of the optimization a second H∞-norm-based cost function measuring the fit between the local information (represented by the locally-estimated LTI models) and the local behavior of a parameterized global LPV model. A special attention is given to parameterized LPV models satisfying a fully-parametrized or a physically-structured linear fractional representation. © 2014, Technical University of Budapest. All rights reserved.


Raddaoui B.,CNRS Laboratory of Computer Science and Automatic Control Systems | Samet A.,Tunis el Manar University
ICAART 2016 - Proceedings of the 8th International Conference on Agents and Artificial Intelligence | Year: 2016

Modern real-world applications are forced to deal with inconsistent, unreliable and imprecise information. In this setting, considerable research efforts have been put into the field of caring for the intrinsic imprecision of the data. Indeed, several frameworks have been introduced to deal with imperfection such as probabilistic, fuzzy, possibilistic and evidential databases. In this paper, we present an alternative framework, called correlated incomplete database, to deal with information suffering with imprecision. In addition, correlated incomplete database is studied from a data mining point of view. Since, frequent itemset mining is one of the most fundamental problems in data mining, we propose an algorithm to extract frequent patterns from correlated incomplete databases. Our experiments demonstrate the effectiveness and scalability of our framework. Copyright © 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.


Cauet S.,CNRS Laboratory of Computer Science and Automatic Control Systems | Coirault P.,CNRS Laboratory of Computer Science and Automatic Control Systems | Njeh M.,CNRS Laboratory of Computer Science and Automatic Control Systems
Control Engineering Practice | Year: 2013

This paper presents a case of persistent harmonic active control for an HEV (Hybrid Electric Vehicle) powertrain. The active control is adapted for a hybrid powertrain consisting of a one-cylinder diesel engine, coupled with a PMSM (Permanent Magnet Synchronous Machine). The PMSM assures the propulsion of the vehicle, as in conventional mild-hybrid electrical vehicles. In addition, it provides speed ripple reductions of the diesel engine. Due to the HEV speed variation, the active control must match this variation. The speed is introduced as a parameter in order to devise an LPV (linear parameter varying) control strategy. The suitability of LPV control for engine torque ripple reduction is demonstrated through a torque control implementation of the PMSM. The control strategy uses the internal model principle of multi-sinusoidal persistent disturbances. The controller is designed to involve several steps, including LMI-based (Linear Matrix Inequalities) optimization. The results show that, for the first and second orders of the ripple, speed oscillations can be reduced when the speed varies. An industrial test bed is used to validate the effectiveness of the approach and the power consumption of the strategy is analyzed. © 2013 Elsevier Ltd.

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