L-2 State Estimation With Guaranteed Convergence Speed in the Presence of Sporadic Measurements

This paper deals with the problem of estimating the state of a nonlinear time-invariant system in the presence of sporadically available measurements and external perturbations. An observer with a continuous intersample injection term is proposed. Such an intersample injection is provided by a linear dynamical system, whose state is reset to the measured output estimation error whenever a new measurement is available. The resulting system is augmented with a timer triggering the arrival of a new measurement and analyzed in a hybrid system framework. The design of the observer is performed to achieve exponential convergence with a given decay rate of the estimation error. Robustness with respect to external perturbations and L2-external stability from plant perturbations to a given performance output are considered. Computationally efficient algorithms based on the solution to linear matrix inequalities are proposed to design the observer. Finally, the effectiveness of the proposed methodology is shown in an example

A necessary and sufficient condition for total observability of discrete-time linear time-varying systems

This paper deals with the total observability problem of discrete-time linear time-varying systems. In particular, a review and suitable analysis of the state-of-the-art of this emerging area are provided. Subsequently, the total observability problem of discrete-time linear time-varying systems is transformed into the one of checking the rank of a convex sum of matrices. As a result, a new total observability test is proposed, along with a suitable computational strategy. The final part of this paper shows examples regarding observability analysis that clearly exhibit the benefits of using the proposed approach.Postprint (published version

Continuous-discrete time observers for a class of MIMO nonlinear systems

International audienceThe observer design problem for nonlineardynamical systems has received a remarkable attention over thelast four decades. A considerable effort has been devoted to theobserver design for systems that are observable for any inputusing the high gain concept for exponential convergence purposes.It is however worth mentioning that the available results aremainly devoted to the continuous-time measurements case in spiteof some nice contributions concerning the sampled measurementscase. The motivation of this talk consists in addressing theproblem of redesigning a high gain continuous-time observer for aclass of MIMO nonlinear systems that are observable for any inputin the case of non uniformly sampled measurements. This provides ahigh gain continuous-discrete time observer witch is more suitablefrom an engineering practice point of view. Two design features ofthe proposed continuous-discrete time observer are worth to bepointed out. Firstly, the observer is particularly described by aset of differential equations with instantaneous state impulsescorresponding to the measured samples and their estimates and ishence an impulsive system in nature. Secondly, the involvedobserver gain is time-varying and its calibration is achievedthroughout the tuning of two design parameters. A particularemphasis in put on the exponential convergence of the observerprovided that the sampling process is not too fast in a welldefined sense. Moreover, a suitable interpretation of the proposedcontinuous-discrete time observer is given, namely it is shownthat the underlying impulsive system can be put under the form ofa hybrid system witch is synthesized using a continuous-timedesign with an inter sample output predictor. The effectiveness ofthe proposed continuous-discrete time observer is emphasizedthroughout simulation results involving useful observer designproblems

Continuous-Discrete Time Observers for a Class of MIMO Nonlinear Systems

This technical note addresses the observer design problem for a class of continuous-time dynamical systems with non-uniformly sampled measurements. More specifically, we propose an observer that runs in continuous-time with an output error correction term that is updated in a mixed continuous-discrete fashion. The proposed observer is actually an impulsive system since it is described by a set of differential equations with instantaneous state impulses corresponding to the measured samples and their estimates. Nevertheless, we shall show that such an impulsive system can be put under the form of a hybrid system composed of a continuous-time high gain observer coupled with an inter-sample output predictor. Two design features of the proposed observer are worth emphasizing. Firstly, the observer calibration is achieved through the tuning of a scalar design parameter. Secondly, the exponential convergence to zero of the observation error is established under a well-defined condition on the maximum value of the sampling partition diameter. Simulations results involving a flexible joint robot arm are given in order to highlight the performance of the proposed observer

Nouveaux schémas de commande et d'observation basés sur les modèles de Takagi-Sugeno

This thesis addresses the estimation and controller design for continuous-time nonlinear systems. The methodologies developed are based on the Takagi-Sugeno (TS) representation of the nonlinear model via the sector nonlinearity approach. All strategies intend to get more relaxed conditions.The results presented for controller design are split in two parts. The first part is about standard TS models under control schemes based on: 1) a quadratic Lyapunov function (QLF); 2) a fuzzy Lyapunov function (FLF); 3) a line-integral Lyapunov functions (LILF); 4) a novel non-quadratic Lyapunov functional (NQLF). The second part concerns to TS descriptor models. Two strategies are proposed: 1) within the quadratic framework, conditions based on a general control law and some matrix transformations; 2) an extension to the nonquadratic approach based on a line-integral Lyapunov function (LILF) using non-PDC control law schemes and the Finsler’s Lemma; this strategy offers parameter-dependent linear matrix inequality (LMI) conditions instead of bilinear matrix inequality (BMI) constraints for second-order systems. On the other hand, the problem of the state estimation for nonlinear systems via TS models is also addressed considering: a) the particular case where premise vectors are based on measured variables and b) the general case where premise vectors can be based on unmeasured variables. Several examples have been included to illustrate the applicability of the obtained results.Cette thèse aborde l'estimation et la conception de commande de systèmes non linéaires à temps continu. Les méthodologies développées sont basées sur la représentation Takagi-Sugeno (TS) du modèle non linéaire par l'approche du secteur non-linéarité. Toutes les stratégies ont l'intention d'obtenir des conditions plus détendu. Les résultats présentés pour la conception de commande sont divisés en deux parties. La première partie est environ sur les modèles TS standard au titre des schémas de commande basés sur: 1) une fonction de Lyapunov quadratique (QLF); 2) une fonction de Lyapunov floue (FLF); 3) une fonction de Lyapunov intégrale de ligne (LILF); 4) un nouveau fonctionnelle de Lyapunov non-quadratique (NQLF). La deuxième partie concerne des modèles TS descripteurs. Deux stratégies sont proposées: 1) dans le cadre quadratique, des conditions basées sur une loi de commande général et quelques transformations de matrices; 2) une extension de l'approche non quadratique basée sur LILF utilisant un schéma de commande non-PDC et le lemme du Finsler; cette stratégie offre conditions sur la forme d’inégalité matricielles linéaires (LMI) dépendant des paramètres au lieu des contraintes sur la forme d’inégalité matricielles bilinéaires (BMI) pour les systèmes de second ordre. D'autre part, le problème de l'estimation de l'état pour les systèmes non linéaires via modèles TS est également abordé considérant: a) le cas particulier où les vecteurs prémisses sont basées sur les variables mesurées et b) le cas général où les vecteurs prémisse peuvent être basés sur des variables non mesurées. Plusieurs exemples ont été inclus pour illustrer l'applicabilité des résultats obtenus

Multi-Rate Observers for Model-Based Process Monitoring

Very often, critical quantities related to safety, product quality and economic performance of a chemical process cannot be measured on line. In an attempt to overcome the challenges caused by inadequate on-line measurements, state estimation provides an alternative approach to reconstruct the unmeasured state variables by utilizing available on-line measurements and a process model. Chemical processes usually possess strong nonlinearities, and involve different types of measurements. It remains a challenging task to incorporate multiple measurements with different sampling rates and different measurement delays into a unified estimation algorithmic framework. This dissertation seeks to present developments in the field of state estimation by providing the theoretical advances in multi-rate multi-delay observer design. A delay-free multi-rate observer is first designed in linear systems under asynchronous sampling. Sufficient and explicit conditions in terms of maximum sampling period are derived to guarantee exponential stability of the observer, using Lyapunov’s second method. A dead time compensation approach is developed to compensate for the effect of measurement delay. Based on the multi-rate formulation, optimal multi-rate observer design is studied in two classes of linear systems where optimal gain selection is performed by formulating and solving an optimization problem. Then a multi-rate observer is developed in nonlinear systems with asynchronous sampling. The input-to-output stability is established for the estimation errors with respect to measurement errors using the Karafyllis-Jiang vector small-gain theorem. Measurement delay is also accounted for in the observer design using dead time compensation. Both the multi-rate designs in linear and nonlinear systems provide robustness with respect to perturbations in the sampling schedule. Multi-rate multi-delay observer is shown to be effective for process monitoring in polymerization reactors. A series of three polycondensation reactors and an industrial gas-phase polyethylene reactor are used to evaluate the observer performance. Reliable on-line estimates are obtained from the multi-rate multi-delay observer through simulation