Didier Maquin

• Professor
• Emeritus Professor at University of Lorraine

Multi-task learning technologies have been developed to be an effective way to improve the generalization performance by training multiple related tasks simultaneously. The determination of the relatedness between tasks is usu- ally the key to the formulation of a multi-task learning method. In this paper, we make the assumption that when tasks are...

Linear parameter varying (LPV) models are being increasingly used as a bridge between linear and nonlinear models. From a mathematical point of view, a large class of nonlinear models can be rewritten in LPV or quasi-LPV forms easing their analysis. From a practical point of view, that kind of model can be used for introducing varying model paramet...

The problem of reducing vibrations during continuous hot-dip galvanizing process is addressed. Using the finite difference method the concerned part of the steel production line is modeled by a state space version of the axially moving strip equation which takes into account disturbances that may affect its efficient functioning. The synthesis of a...

Health-aware control (HAC) has emerged as one of the domains where control synthesis is sought based upon the failure prognostics of system/component or the Remaining Useful Life (RUL) predictions of critical components. The fact that mathematical dynamic (transition) models of RUL are rarely available, makes it difficult for RUL information to be...

This paper proposes a monitoring method for defect detection and localization in a structure operating under environmental and operational conditions (EOCs) variation. This method is based on a model obtained using PCA of the healthy state data. To account for variation in EOCs, more particularly temperature change, the model is updated using a mov...

In several model-based system maintenance problems, parameters are used to represent unknown characteristics of a component, equipment degradation, etc. This allows for modelling constant, slow-varying terms. The identifiability of these parameters is an important condition to estimate them. Linear Parameter Varying (LPV) models are being increasin...

Health-aware control (HAC) has emerged as one of the domains where control synthesis is sought based upon the failure prognostics of system/component or the Remaining Useful Life (RUL) predictions of critical components. The fact that mathematical dynamic (transition) models of RUL are rarely available, makes it difficult for RUL information to be...

This paper proposes two improvements in the design of unknown input observers (UIO) for linear parameter varying (LPV) systems. First, the parameter dependency of the UIO is not restricted to mimic the one of the system in order to relax the existing decoupling conditions. Second, the output equation of the LPV systems is not supposed to be linear...

This paper suggests a Structural Health Monitoring (SHM) method for damage detection and localization in pipeline. The baseline signals, used in SHM, could change due to the variation of environmental and operational conditions (EOCs). Hence, the damage detection method could give rise to false alarm. In this study, this issue is addressed by estim...

Artificial intelligence using machine learning techniques has become omnipresent in different field of studies. Structural health monitoring is an emerging field which should take advantage of these techniques in order to be efficient and more reliable. It aims mainly at detecting and localizing damage in structures automatically without the need o...

Pipelines are very critical structures, especially those used for transporting oil, gas and other chemical substances. To ensure better working conditions of these structures, they must be monitored on a regular basis. Structural health monitoring (SHM) systems were proposed to tackle this issue. They aim at detecting, localizing and estimating the...

System diagnosis has been of a great interest for all aspects of industrial processes more precisely to gain in quality. It is based essentially on the analysis of the links between the variables of a system and more precisely on the changes of the relations between these variables, which testify to the presence of faults or anomalies. For that pur...

Les structures tubulaires telles que les pipelines sont très utilisés pour notamment le transport de gaz et pétrole. Ces structures sont exposées aux problèmes de corrosion et de fatigue mécanique. Le besoin de prolongation de la durée de vie de ces structures peut nécessiter dans certains cas la mise en place d’un système de monitoring, offrant di...

We discuss a design approach for nonlinear discrete-time adaptive observer. This involves transforming a nonlinear system into a quasi-LPV (Linear Parameter Varying) polytopic model in Takagi-Sugeno (T-S) form using nonlinear embedding and sector nonlinearity (SNL) transformation. We then develop a discrete-time counterpart for a joint state and pa...

The objective of this study is the analysis of dynamic systems represented by a multimodel expression with variable parameters. Changes in these parameters are unknown but bounded. Since it is not possible to estimate these parameters over time, the simulation of such systems requires the consideration of all possible values taken by these paramete...

This paper focuses on the development of a method for damage detection and localization in pipeline structures. These structures are subject to variation of environmental and operational conditions (EOCs) which have an impact on the collected signals. Since damage detection is generally based on comparison between the reference signals and the curr...

In this paper, a new strategy to cope with unmeasurable premise variables in observer design for Takagi-Sugeno (TS) models is proposed. The guiding principles are the immersion techniques and auxiliary dynamics generation, allowing to immerge a given TS system with unmeasured state dependent weighting functions into a larger TS system with weightin...

Takagi-Sugeno (T-S) type of polytopic models have been used prominently in the literature to analyze nonlinear systems. With the sector nonlinearity approach, an exact representation of a nonlinear system within a sector could be obtained in a T-S form. Hence, a number of observer design strategies have been proposed for nonlinear systems using the...

The principal component analysis (PCA) is a linear technique widely used to retrieve a subspace that maximizes the variance of the data, making the presence of a fault easy to detect. Nevertheless, the real systems are nonlinear. To this end, we propose in this paper to use a kernel-based technique known as kernel principal component analysis (KPCA...

We discuss a design approach for nonlinear discrete-time adaptive observer. This involves transforming a nonlinear system into a quasi-LPV (Linear Parameter Varying) polytopic model in Takagi-Sugeno (T-S) form using nonlinear embedding and sector nonlinearity (SNL) transformation. We then develop a discrete-time counterpart for a joint state and pa...

Takagi-Sugeno (T-S) models have been popular in analyzing nonlinear systems. Observer designs for T-S models have focused on both cases with measured and unmeasured premise variables. However, the unmeasured premise variables have to be one of the states of the system. If one of the inputs is a premise variable, these approaches are not applicable....

Les approches SHM (Structural Health Monitoring) ont été proposées pour répondre au besoin de surveiller en permanence l’état de santé des structures. Cela permet d’anticiper la détection de dégradations et par conséquent d’éviter les accidents ou les arrêts de fonctionnement. Pour ce faire, ces approches reposent sur l’utilisation des techniques d...

Variable Air Volume (VAV) based Heating Ventilation and Air Conditioning (HVAC) systems are common in large non-residential buildings. The dynamic model of a VAV system along with the Air Handling Unit (AHU) and the zones has a nonlinear characteristic. In this paper, a nonlinear model based joint state and parameter observer is proposed to estimat...

Process monitoring needs the development of data analysis tools aiming at recognizing, at each time instant, system operating mode using the measurement collected on the system. This communication aims at presenting a method relying on measurement analysis, able to identify operating modes without the knowledge of the mathematical models describing...

This paper addresses a new method to overcome the unmeasurable premise variables in TS nonlinear discrete time systems for observer design. It is known that a TS system can be obtained directly from a nonlinear one by using the sector nonlinear transformation in a given compact set of the state space. However, this procedure often leads to TS syste...

Feature selection techniques aim to evaluate feature's importance and select the most relevant ones. This paper concerns the selection of features in order to perform a reliable Structural Health Monitoring by means of ultrasonic guided waves technique. The current case of study deals with the health monitoring of pipelines. A corrosion-like defect...

Structural Health Monitoring (SHM) aims to assess the integrity of structures. This can be achieved by means of various nondestructive testing techniques. It is based on sensors and actuators that are designed to live permanently with the structures to be monitored. These structures should be interrogated regularly during a period long enough to bu...

In the present paper, a Takagi–Sugeno (TS) model is used to simultaneously represent the behaviour of a nonlinear system and its saturated actuators. With the TS formalism and the Lyapunov approach, stabilization conditions are expressed as linear matrix inequalities for different controller designs. Static parallel distributed compensation (PDC) s...

In the present paper, a Takagi-Sugeno (T-S) model is used to simultaneously represent the behaviour of a nonlinear system and its saturated actuators. With the T-S formalism and the Lyapunov approach, stabilization conditions are expressed as Linear Matrix Inequalities (LMIs) for different controller designs. Static Parallel Distributed Compensatio...

A new actuator fault diagnosis and estimation approach is proposed for dynamical systems. The main contribution consists in enhancing the fault detection with a new observer that takes into account the relative degree of the output of the system with respect to the fault. The Single Input Single Fault (SIFO) case is considered to present the approa...

Air Handling Units (AHU) are responsible for efficiently transferring the energy produced for heating or cooling to the occupant area in the building. This energy transfer dynamics is modeled as a bilinear system. Such a structure poses problems to develop observers either with asymptotically vanishing error or with guaranteed error bounds. Takagi-...

Cet article se place dans le cadre du monitoring des structures et traite principalement la technique des ondes ultrasonores guidées. Il porte sur la classification des données de cette technique par le biais des séparateurs à vaste marge, dont la fiabilité est conditionnée par la sélection ciblée des paramètres du séparateur optimal. Différents al...

In terms of system diagnosis, several studies are generally performed. The diagnosis is composed of three different parts: detecting, isolating and estimating the value of the faults. If many results have been obtained for linear systems with a known model, the situation is quite different in the case of nonlinear systems behavior, especially when...

This paper addresses a discussion about Unknown Input Observers (UIO) for Linear Parameter Varying (LPV) systems designed classically by using the polytopic representation. It is illustrated that even if the rank conditions ensuring the existence of an UIO are satisfied, the design may fail, due to the polytopic representation of the LPV system. In...

The principal component analysis (PCA) is a well-known technique to detect, isolate and estimate faults affecting a system. However, PCA identifies only linear structures in a given dataset. In this paper, we propose a new technique to estimate the fault affecting nonlinear systems, within the frame of kernel machines. To this end, the kernel metho...

This work addresses the model reference tracking control problem. It aims to highlight the encountered difficulties and the proposed solutions to achieve the tracking objective. Based on a literature overview of linear and nonlinear reference tracking, the achievements and the limitations of the existing strategies are highlighted. This motivates t...

This paper presents a new scheme for sensor fault tolerant control for nonlinear systems based on the Takagi–Sugeno modeling. First, a structured residual generator aimed at detecting and isolating sensor faults is designed. A bank of observers controlled either by only one system output or a set of outputs is then implemented, leading to a set of...

Building Energy Management System (BEMS) plays a crucial role in overall energy savings of a building and hence that of the country. BEMS focuses on providing the necessary comfort to the occupants as well as reducing the energy consumed. One of the key aspects of energy management is to identify faults in order to avoid lack of comfort or increase...

Reports on the 2014 IEEE Multiconference on Systems and Control.

Technological advances in the process industries during the past decade have resulted in increasingly complicated processes, systems and products. Therefore, recent researches consider the challenges in their design and management for successful operation. While principal component analysis (PCA) technique is widely used for diagnosis, its structur...

This work addresses the model reference tracking control problem. It aims to highlight the encoutered difficulties and the proposed solutions to achieve the tracking objective for nonlinear systems described by Takagi-Sugeno (T-S) models. Different control strategies are exposed. Exact state tracking is proposed and structural conditions for it are...

This paper addresses the Finite Memory Observer (FMO) design applied to polytopic models. After a brief introduction on FMO for linear systems, the nonlinear models represented in a Takagi-Sugeno (T-S) or Polytopic form are then considered. The considered observer design will be applied to investigate the fault diagnosis for nonlinear discrete-time...

Many innovations are currently initiated by scientific community in the field of dynamic system diagnosis. Arcelormittal Maizières R&D adapted and evaluated some advanced diagnosis tools for the detection of abnormal events and operating mode changing in steel processes. The developed approach is illustrated and applied to the sticker detection in...

A framework for the joint design of online sensor scheduling and fault detection is proposed. First, the synthesis of fault detection filter under any event triggering mechanism is given. The proposed filter can be viewed as a special structure of the Bayesian filter. To demonstrate its performance, this filter is tested under mixed event triggerin...

Modeling, analysis and control of networked control systems (NCS) have recently emerged as topics of significant interest to the control community. The defining feature of any NCS is that information is exchanged using digital band-limited serial communication channel among systems components and usually shared by other feedback control loops. Conv...

Plenary talk

This paper addresses the state and sensor fault estimation for nonlinear systems represented by Takagi-Sugeno (T-S) models. The considered faults are time-varying and with multiplicative effect on the sensor output signals. The proposed estimation procedure is based firstly on the sector nonlinearity approach using the convex polytopic transformati...

System often has several operating modes that are controlled by the operator to follow a desired change or not in the case of fault occurrence or change due to the environment of the system. The challenge is to be able to know the current operating mode in order to apply the appropriate controls. The aim of this work is to recognise the active mode...

Multiple models are recognised by their abilities to accurately describe nonlinear dynamic behaviours of a wide variety of nonlinear systems with a tractable model in control engineering problems. Multiple models are built by the interpolation of a set of submodels according to a particular aggregation mechanism, with the heterogeneous multiple mod...

This paper considers the problem of fault tolerant control (FTC) by trajectory tracking for uncertain nonlinear system described by Takagi-Sugeno models. The considered faults are constant, exponential or polynomial. The provided results are easily formulated in terms of Linear Matrix Inequalities by employing the descriptor redundancy property. Th...

This work concerns the model reference tracking control problem for nonlinear systems represented by Takagi-Sugeno (T-S) models, with a guaranteed L2 performance to attenuate the tracking error for bounded reference inputs. The objective is to make the system states follow as closely as possible the model reference states. The control scheme is bas...

This paper addresses the stabilization of nonlinear systems described by Takagi-Sugeno models affected by input actuator saturation. A parallel distributed compensation design is used for the state feedback controller. Stabilization conditions in the sense of the Lyapunov method are derived and expressed as a linear matrix inequality problem. The o...

The main contribution of this paper is to propose a systematic approach to the observers design for nonlinear Takagi-Sugeno (T-S) time-varying systems. The proposed procedure is based on the sector nonlinearity approach using the convex polytopic transformation. It guarantees global convergence for joint state and parameter estimation error and is...

In this paper, a Takagi-Sugeno model is used to represent the nonlinear behaviour of an actuator with saturation constraint. The control design is based on an output feedback controller (static and dynamic) depending on the saturation levels. Stabilization conditions are derived with the Lyapunov method and expressed in terms of linear matrix inequ...

This paper deals with nonlinear systems control with input saturation and parametric uncertainties. The considered nonlinear systems are represented by Takagi-Sugeno models. The proposed controller is a parallel distributed compensation state feedback. Stabilization conditions are derived with the Lyapunov method and expressed as an optimization pr...

A systematic approach to joint state and time-varying parameter estimation for nonlinear systems is proposed in this paper. Applying the sector nonlinearity transformation to both the system nonlinearities and the time-varying parameters, the original system is equivalently rewritten as a Takagi–Sugeno system with unmeasurable premise variables. A...

This article is dedicated to the problem of fault detection, isolation and estimation for nonlinear systems described by a Takagi–Sugeno (T–S) model. One of the interests of this type of models is the possibility to extend some tools and methods from the linear system case to the nonlinear one. The principle of the proposed strategy is to transform...

Multiple models are recognised by their abilities to accurately describe nonlinear dynamic behaviours of a wide variety of nonlinear systems with a tractable model in control engineering problems. Multiple models are built by the interpolation of a set of submodels according to a particular aggregation mechanism, with the heterogeneous multiple mod...

The contribution of this paper is to propose a systematic approach to the observer design for linear time-varying systems. It is based on the exact rewriting of the original time-varying system into a polytopic linear model (PLM). This transformation uses the sector nonlinearity approach based on the convex polytopic transformation. Then a joint st...

This paper addresses the problem of multiple fault detection and isolation under communication constraints. More specifically, we consider the issue of sensor scheduling and fault isolation co-design under limited bandwidth capacity. The proposed isolation filter can be viewed as special structure of the traditional Kalman filter. The sensor schedu...

In this paper, the problem of observer design for nonlinear Lipschitz systems is treated. An emphasis is put on maximizing the admissible Lipschitz constant for which the observer design is possible. This problem is tackled using a Takagi-Sugeno modeling approach. The idea is to re-write the state estimation error dynamics as an autonomous Takagi-S...

The problem of observer design for nonlinear Lipschitz systems is dealt with in this work. An emphasis is put on the maximization of the admissible Lipschitz constant for which the observer design is possible. This problem is tackled using a Takagi-Sugeno modeling approach. The idea is to rewrite the state estimation error dynamics as an autonomous...

This paper addresses the problem of state and clinker hardness estimation in a cement mill process. A Takagi-Sugeno model with unmeasurable premise variables is developed for a nonlinear model of a cement mill. Based on this model, a nonlinear observer is proposed in order to estimate the state variables and also the clinker hardness, which is an u...

This paper deals with the problem of sensor fault tolerant control for Takagi-Sugeno nonlinear systems. Firstly, a residual generator is designed in order to detect and isolate sensor faults. Secondly, a nonlinear observer based controller, adopting the so-called parallel distributed compensation structure is designed. This controller is based on a...

This chapter presents a new approach to multitask learning (MTL) that relies on one-class support vector machines (1-SVMs). A 1-SVM focuses only on the estimation of the envelope of a region containing the samples of the target class, the envelope being sufficient for classification. First, the chapter briefly describes the formulation of a one-cla...

This paper proposes an automatic method for artefact removal and noise elimination from scalp electroencephalogram recordings (EEG). The method is based on blind source separation (BSS) and supervised classification and proposes a combination of classical and news features and classes to improve artefact elimination (ocular, high frequency muscle a...

In this paper, the Takagi-Sugeno representation is used to represent the nonlinear behaviour of a saturated actuator. The control design is based on a state feedback con-troller function of the saturation levels. Stabilization conditions in the sense of Lyapunov method are derived and expressed as a linear matrix inequality problem. An academic exa...

This paper proposes a new approach of observer design for nonlinear systems described by a Takagi-Sugeno model. Its main contribution concerns models with premise variables depending on the system states which are completely or partially unknown. This case is more difficult than when the premise variables are known or measured. Indeed, in this case...

New fault tolerant control strategies for nonlinear Takagi-Sugeno systems New methodologies for Fault Tolerant Control (FTC) are proposed in order to compensate actuator faults in nonlinear systems. These approaches are based on the representation of the nonlinear system by a Takagi-Sugeno model. Two control laws are proposed requiring simultaneous...

This paper deals with state estimation for linear discrete-time systems subject to unknown input. Although many papers have dealt with the problem of Unknown Input Observer design, state decoupling and reconstruction ; the goal is to present a new method allowing to characterize a class of unknown inputs to which the estimation error is decoupled....

This paper deals with the problem of sensor fault estimation for linear and nonlinear systems. Thanks to the introduction of an augmented generalized state vector, including the original state vector and a filtered output of the system, the sensor fault ap- pears as an unknown input. Therefore, an adaptive proportional integral observer is used to...

This paper addresses fault diagnosis for observerbased residual generators for linear discrete-time systems subject to unknown input. The proposed approach is a new method allowing to characterize a class of unknown inputs from which the estimation error is decoupled. This contribution is divided into two parts. The first one concerns the design of...

Un système physique est souvent soumis à des perturbations, non directement mesurables, qui ont pour origines des phénomènes extérieurs dus à l'environnement, ou des phénomènes internes liés à des modifications du système. Ces perturbations que l'on peut assimiler à des entrées inconnues (EIs) ont des effets néfastes sur le comportement du système,...

This paper deals with the problem of fault tolerant control of nonlinear systems represented by Takagi-Sugeno models subject to sensor faults. Observer based controllers are designed for each faulty-situation (mode). The classical switching law is replaced by a new mechanism which avoid the switching phenomenon. The purpose is to be able to study t...

Un système physique est souvent soumis à des perturbations, non directement mesurables, qui ont pour origines des phénomènes extérieurs dus à l'environnement, ou des phénomènes internes liés à des modifications du système. Ces perturbations que l'on peut assimiler à des entrées inconnues (EIs) ont des effets néfastes sur le comportement du système,...

Classical machine learning technologies have achieved much success in the learning of a single task at a time. However, in many practical applications we may need to learn a number of related tasks or to rebuild the model from new data, for example, in the problem of fault detection and diagnosis of a system that contains a set of equipments a prio...

Il s'agit d'étudier une ou plusieurs méthodes de classification de données dans le but de définir un système de diagnostic ou de surveillance générique d'un parc de machines ou plus généralement de systèmes. Dans le cas considéré, les données expertisées viennent de plusieurs éléments du parc. Elles constituent l'ensemble d'apprentissage de départ....