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Publications de l'équipe DISCO

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835documents trouvés

13403
01/10/2017

Improved solutions for ill-conditioned problems involved in set-membership estimation for fault detection and isolation

L.RAVANBOD, C.JAUBERTHIE, N.VERDIERE, L.TRAVE-MASSUYES

Université du Havre, DISCO

Revue Scientifique : Journal of process control, Vol.58, pp.139-151, Octobre 2017 , N° 13403

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Abstract

Set-membership (SM) estimation implies that the computed solution sets are guaranteed to contain all the feasible estimates consistent with the bounds specified in the model. Two issues often involved in the solution of SM estimation problems and their application to engineering case studies are considered in this paper. The first one is the estimation of derivatives from noisy signals, which in a bounded uncertainty framework means obtaining an enclosure by lower and upper bounds. In this paper, we improve existing methods for enclosing derivatives using Higher-Order Sliding Modes (HOSM) differentiators combining filtering. Our approach turns the use of high order derivatives more efficiently especially when the signal to differentiate has slow dynamics. The second issue of interest is solving linear interval equation systems, which is often an ill-conditioned problem. This problem is reformulated as a Constraint Satisfaction Problem and solved by the combination of the constraint propagation Forward Backward algorithm and the SIVIA algorithm. The two proposed methods are tested on illustrative examples. The two methods are then used in a fault detection and isolation algorithm based on SM parameter estimation that is applied to detect abnormal parameter values in a biological case study.

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17304
18/09/2017

ARMISCOM: self-healing service composition

J.VIZCARRONDO, J.AGUILAR, E.EXPOSITO, A.SUBIAS

CENDITEL, Andes, LIUPPA, DISCO

Revue Scientifique : Service Oriented Computing and Applications, Vol.11, N°3, pp.345-365, Septembre 2017 , N° 17304

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Abstract

In the domain of the service composition, the failure of a service generates error propagation in the other services, and therefore, it can generate the failure of the entire system. Usually, these failures cannot be detected and corrected only with local information. Normally, it is required the development of architectures that enable the diagnosis and correction of faults, both locally (elementary service) as well as globally (service composition). This paper presents a reflexive middleware architecture based on autonomic computing, which allows the distributed diagnosis of faults in the service composition, called ARMISCOM. This middleware has not a central diagnoser, instead the diagnosis of failures is carried out through the interaction of local diagnosers present in each service of the composition. These local diagnoses use a distributed chronicle approach proposed in previous works, which allows the recognition of fully distributed patterns of the classic failures in the SOA systems. In addition, the repair strategies are defined through consensus of the repairers, equally distributed between the services of the composition. The repair strategies use the concept of “equivalent regions” defined in this paper, for the fault correction in a SOA application.

140857
17153
17/08/2017

A learning algorithm for episodes

T;OBRY, A.SUBIAS, L.TRAVE-MASSUYES

DISCO

Rapport LAAS N°17153, Août 2017, 5p.

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140156
17155
17/08/2017

Diagnostic de motifs de comportements dans les systèmes temporels

Y.PENCOLE, A.SUBIAS

DISCO

Rapport LAAS N°17155, Août 2017, 14p.

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140158
17154
17/08/2017

Diagnosis of supervision patterns on bounded labeled Petri nets by model checking

Y.PENCOLE, A.SUBIAS

DISCO

Rapport LAAS N°17154, Août 2017, 9p.

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140157
17141
26/07/2017

Unknown input reconstruction: a comparison of system inversion and sliding mode observer based techniques

M.ZHANG, Z.LI, M.CABASSUD, B.DAHHOU

GUIZHOU, LGC, DISCO

Manifestation avec acte : Chinese Control Conference ( CCC ) 2017 du 26 juillet au 28 juillet 2017, Dalian (Chine), Juillet 2017, 7p. , N° 17141

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17228
14/07/2017

Interval Kalman filter enhanced by positive definite upper bounds

T.A.TRAN, C.JAUBERTHIE, F.LE GALL, L.TRAVE-MASSUYES

DISCO

Manifestation avec acte : IFAC World Congress 2017 du 09 juillet au 14 juillet 2017, Toulouse (France), Juillet 2017, pp.1631-1636 , N° 17228

Lien : https://hal.laas.fr/hal-01561951

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Abstract

A method based on the interval Kalman filter for discrete uncertain linear systems is presented. The system under consideration is subject to bounded parameter uncertainties not only in the state and observation matrices, but also in the covariance matrices of Gaussian noises. The gain matrix provided by the filter is optimized to give a minimal upper bound on the state estimation error covariance for all admissible uncertainties. The state estimation is then determined by using interval analysis in order to enclose the set of all possible solutions with respect to the classical Kalman filtering structure.

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17284
14/07/2017

Fault-driven structural diagnosis approach in a distributed context (I)

C.PEREZ, E.CHANTHERY, L.TRAVE-MASSUYES, J.SOTOMAYOR

DISCO, PUCP

Manifestation avec acte : IFAC World Congress 2017 du 09 juillet au 14 juillet 2017, Toulouse (France), Juillet 2017, pp.14819-14824 , N° 17284

Lien : https://hal.archives-ouvertes.fr/hal-01579467

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Abstract

Distributed diagnosis is important for complex systems as a way to reduce computational costs or for large systems that require minimizing data transfer. This paper presents a distributed diagnosis method for continuous systems that only requires the knowledge of local models and limited knowledge of their neighboring subsystems. The notion of Fault Driven Minimal Structurally Overdetermined (FMSO) set is used as the corner stone of the design of residual generators. We show that all the FMSO sets of the global system can be obtained in a distributed manner from so-called shared FMSO sets and shared CMSO sets that are computed along a structural approach for every local site.

140738
16466
14/07/2017

Enhanced chronicle learning for process supervision

J.VASQUEZ, L.TRAVE-MASSUYES, A.SUBIAS, F.JIMENEZ

DISCO, Andes

Manifestation avec acte : IFAC World Congress 2017 du 09 juillet au 14 juillet 2017, Toulouse (France), Juillet 2017, pp.5191-5196 , N° 16466

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Abstract

Process alarm management can be approached as a pattern recognition problem in which temporal patterns are used to characterize different typical situations, particularly at startup and shutdown stages. This paper focuses on learning the temporal patterns, in the form of chronicles, by extending the previously proposed Heuristic Chronicle Discovery Algorithm Modified HCDAM . The proposed extension incorporates knowledge, in particular in the form of so called temporal runs, to focus the learning process and produce less conservative chronicles. The resulting Chronicle Based Alarm Management (CBAM) approach is hence based on a diagnosis process which permits situation recognition and provides the operators with relevant information about the failures inducing alarms flows in the startup and shutdown stages. The event sequences that represent a process situation are generated by simulation; moreover, including temporal runs, the chronicles are extracted using the extended version of HCDAM.

140674
17194
14/07/2017

Design of indicators for the detection of time shift failures in (max, +)-linear systems

A.SAHUGUEDE, E.LE CORRONC, Y.PENCOLE

DISCO

Manifestation avec acte : IFAC World Congress 2017 du 09 juillet au 14 juillet 2017, Toulouse (France), Juillet 2017, 7p. , N° 17194

Lien : https://hal.laas.fr/hal-01534552

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Abstract

In this paper, we address the problem of failure detection in a timed discrete event system (TDES). We first introduce the problem of detecting time shift failures in a TDES modeled as a (max, +)-linear system. Then we propose the definition of an indicator that relies on the (max, +) algebraic framework and show how it can detect time shift failures in the case of a single output system. Finally, an extension is proposed to deal with multiple outputs.

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