Intelligent Prognostic Framework for Degradation Assessment and Remaining Useful Life Estimation of Photovoltaic Module

All industrial systems and machines are subjected to degradation processes, which can be related to the operating conditions. This degradation can cause unwanted stops at any time and major maintenance work sometimes. The accurate prediction of the remaining useful life (RUL) is an important challenge in condition-based maintenance. Prognostic activity allows estimating the RUL before failure occurs and triggering actions to mitigate faults in time when needed. In this study, a new smart prognostic method for photovoltaic module health degradation was developed based on two approaches to achieve more accurate predictions: online diagnosis and data-driven prognosis. This framework of forecasting integrates the strengths of real-time monitoring in the first approach and relevant vector machine in the second. The results show that the proposed method is plausible due to its good prediction of RUL and can be effectively applied to many systems for monitoring and prognostics

A new method for Project risk identification: Case study of a real construction project

Abstract: Compared with many other sectors, a construction project is a subject to more risks due to its specific characteristics such as long period, complicated processes, abominable environment, financial intensity and dynamic organization structure. Managing risks is recognized as a very important management process in order to assure its successful delivery. It aims at identifying sources of risk and uncertainty, determining their impact, and developing appropriate management response. This paper presents a new method called "ThreeDimensional Risk Identification" (TRI) proposed for the identification of a construction project risks. A case study of a real construction project is used to illustrate this approach

An integrated way to design FD/FTC modules via parity space and model following

International audienceThis paper deals with the problem of integration of fault diagnosis and fault tolerant control modules. The main objective is to ensure a good behavior of the closed-loop system in the presence of faults and disturbances. To this aim, a global active methodology is defined in order to synthesize an additive optimal control input from fault detection and isolation results. More precisely, a robust residual is firstly generated by means of usual parity relations to detect and isolate faults on the system. Next, a fault accommodation procedure, based model following control scheme, is used to generate an additive control input according to the residual characteristics. The efficiency of this methodology is illustrated through an heating system benchmark

Génération de résidus directionnels pour le diagnostic des systèmes linéaires stochastiques et la commande

F. Kratz (Président), C. Commault (rapporteur), G. Gissinger (rapporteur), M. Ouladsine, D. Sauter (directeur de thèse), J. Y. Keller (co-encadrant)The main work presented in this document deals with the synthesis of a diagnosis method and a fault tolerant control law for linear stochastic systems. It is divided into two parts: - the first part concerns the design of robust fault detection filter. It has been defined in such a way that the obtained directional residual sensitivity to model and stochastic uncertainties is minimally. This approach is different from the existant ones because the fault detection filter is designed on the basis of a system inversion. After having parametrized all the minimum-time left-inverses of the system, the remaining available degrees of freedom have been computed to maximize the fault signal-to-noise ratio. This approach has allowed to define an optimal filtering of the reduced state having maximal dimension. In other words, the fault effect on the state estimation error is maximally reduced under the constraint that sufficient information remains available to detect and isolate the faults. - the second part deals with the integration of the fault detection filter into the fault tolerant control law. The deadbeat structure of detection space allows to obtain two fault tolerant control laws having maximum reactivity. The first is based on the augmented fault detection filter and on the well-known separation principle in the LQG technique. The control law is obtained by rejecting the non controllable modes. This approach has led to LTR control (Left Transfer Recovery) obtained by an explicit computation of the system left-inverse. Like the first approach, the second law is also based on the fault detection filter but it is characterized by the optimal definition of an additive control law. Its application to a benchmark defined in the IFATIS project has shown the best reactivity of this control law after the abrupt occurence of both single and multiple faults. The proposed control law allows to accommodate the fault effects faster than a Proportional Integral control law which always reacts slower.Ce travail porte sur le diagnostic et la commande tolérante aux défauts des systèmes linéaires stochastiques. Il se décompose en deux parties: - la première phase du travail présenté porte sur la conception d'un filtre de détection robuste. Il a été défini afin que le résidu directionnel qui en résulte soit le plus insensible possible aux incertitudes de modèle et aux incertitudes stochastiques. L'approche développée diffère des approches classiques existant dans la littérature car le filtre de détection est synthétisé sur la base d'une inversion du système. Une fois paramétrées toutes les inverses à gauche du système (pour remonter à la source des défauts) grâce à l'étude de la structure des zéros infinis du système, les degrés de liberté restant à disposition sont utilisés pour minimiser la sensibilité du résidu généré aux différentes perturbations stochastiques. Cette approche a permis de définir le filtrage d'état optimal d'une partie réduite du vecteur d'état du système de dimension maximale. En d'autres termes, l'effet des défauts sur l'erreur d'estimation d'état du filtre a été réduite à son maximum sous la contrainte que suffisamment d'informations restent disponibles pour les détecter et les localiser dans l'espace de sortie. - la deuxième partie concerne l'intégration du filtre de détection dans une commande tolérante aux défauts. La structure deadbeat de l'espace de détection du filtre est à la base de la conception de deux lois de commande tolérantes aux défauts à réactivité maximale. La première est basée sur le filtre de détection à état augmenté et sur le principe de séparation bien connu dans le cadre LQG. La loi de commande a été obtenue par un rejet des modes non contrôlables. Cette approche a débouché sur une commande de type LTR (Left Transfer Recovery) obtenue par le calcul explicite de l'inverse à gauche du système. Tout comme la première approche, la deuxième loi de commande se fonde sur le filtre de détection mais se caractérise par la définition optimale d'une loi de commande additive. Son application à un benchmark défini dans le cadre du projet IFATIS (Intelligent Fault Tolerant Control in Integrated Systems) a permis de mettre en avant la forte réactivité de la commande face à l'apparition brutale d'un ou de plusieurs défauts sur le système. Il s'avère en effet que la commande mise en oeuvre permet d'annuler plus rapidement les effets néfastes engendrés par les défauts en comparaison d'une commande de type PI standard toujours plus lente à réagir

Lithium-ion Battery Degradation Assessment and Remaining Useful Life Estimation in Hybrid Electric Vehicle

<p class="Abstract"><em>Abstract</em>—Prognostic activity deals with prediction of the remaining useful life (RUL) of physical systems based on their actual health state and their usage 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.</p

Génération de résidus directionnels pour le diagnostic des systèmes linéaires stochastiques et la commande tolérante aux défauts

Le travail présenté dans ce mémoire porte sur le diagnostic et la commande tolérante aux défauts des systèmes linéaires stochastiques. Il se décompose en deux parties: - la première phase du travail présenté porte sur la conception d'un filtre de détection robuste. Il a été défini afin que le résidu directionnel qui en résulte soit le plus insensible possible aux incertitudes de modèle et aux incertitudes stochastiques. L'approche développée diffère des approches classiques existant dans la littérature car le filtre est synthétisé sur la base d'une inversion du système.- la deuxième partie concerne l'intégration du filtre de détection dans une commande tolérante aux défauts. La structure deadbeat de l'espace de détection du filtre est à la base de la conception d'une loi de commande tolérante aux défauts à réactivité maximale. Son application à un benchmark a permis de mettre en avant la forte réactivité de la commande face à l'apparition brutale des défauts sur le système.The main work presented in this document deals with the synthesis of a diagnosis method and a fault tolerant control law for linear stochastic systems. It is divided into two parts: - the first part concerns the design of robust fault detection filter. It has been defined in such a way that the obtained directional residual sensitivity to model and stochastic uncertainties is minimally. This approach is different from the existant ones because the fault detection filter is designed on the basis of a system inversion. - the second part deals with the integration of the fault detection filter into the fault tolerant control law. The deadbeat structure of detection space allows to obtain a fault tolerant control laws having maximum reactivity. Its application to a benchmark defined in the IFATIS project has shown the best reactivity of this control law after the abrupt occurence of both single and multiple faults.NANCY1-SCD Sciences & Techniques (545782101) / SudocSudocFranceF

Takagi–Sugeno Fuzzy Control for a Nonlinear Networked System Exposed to a Replay Attack

This article investigates the stabilization problem of a nonlinear networked control system (NCS) exposed to a replay attack. A new mathematical model of the replay attack is proposed. The resulting closed-loop system is defined as a discrete-time Markovian jump linear system (MJLS). Employing the Lyapunov–Krasovskii functional, a sufficient condition for stochastic stability is given in the form of linear matrix inequalities (LMIs). The control law can be obtained by solving these LMIs. Finally, a simulation of an inverted pendulum (IP) with Matlab is developed to illustrate our controller’s efficiency