Results 1  10
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14
Inputtostate stability of networked control systems
 Automatica
, 2004
"... Abstract — A new class of uniformly globally asymptotically stable (UGAS) protocols in networked control systems (NCS) is considered. It shown that if the controller is designed without taking into account the network so that it yields inputtostate stability (ISS) with respect to external disturban ..."
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Cited by 15 (0 self)
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Abstract — A new class of uniformly globally asymptotically stable (UGAS) protocols in networked control systems (NCS) is considered. It shown that if the controller is designed without taking into account the network so that it yields inputtostate stability (ISS) with respect to external disturbances (not necessarily with respect to the error that will come from the network implementation), then the same controller will achieve semiglobal practical ISS for the NCS when implemented via the network with a UGAS protocol. The adjustable parameter with respect to which semiglobal practical ISS is achieved is the socalled maximal allowable transfer interval (MATI) between transmission times. I.
Minimumenergy state estimation for systems with perspective outputs
 IEEE TRANS. ON AUTOMAT. CONTR
, 2003
"... This paper addresses the state estimation of systems with perspective outputs. We derive a minimumenergy estimator which produces an estimate of the state that is “most compatible” with the dynamics, in the sense that it requires the least amount of noise energy to explain the measured outputs. Und ..."
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Cited by 5 (3 self)
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This paper addresses the state estimation of systems with perspective outputs. We derive a minimumenergy estimator which produces an estimate of the state that is “most compatible” with the dynamics, in the sense that it requires the least amount of noise energy to explain the measured outputs. Under suitable observability assumptions, the estimate converges globally asymptotically to the true value of the state in the absence of noise and disturbance. In the presence of noise, the estimate converges to a neighborhood of the true value of the state. These results are also extended to solve the estimation problem when the measured outputs are transmitted through a network. In that case, we assume that the measurements arrive at discretetime instants, are timedelayed, noisy, and may not be complete. We show that the redesigned minimumenergy estimator preserves the same convergence properties. We apply these results to the estimation of position and orientation for a mobile robot that uses a monocular chargedcoupleddevice (CCD) camera mounted onboard to observe the apparent motion of stationary points. In the context of our application, the estimator can deal directly with the usual problems associated with vision systems such as noise, latency and intermittency of observations. Experimental results are presented and discussed.
A Relaxed Criterion for Contraction Theory: Application to an Underwater Vehicle Observer
 in European Control Conference
, 2003
"... On the contrary to Lyapunov theory, contraction theory studies system behavior independently from a specific attractor, thus leading to simpler computations when verifying exponential convergence of nonlinear systems. To check the contraction property, a condition of negativity on the Jacobian of th ..."
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Cited by 4 (3 self)
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On the contrary to Lyapunov theory, contraction theory studies system behavior independently from a specific attractor, thus leading to simpler computations when verifying exponential convergence of nonlinear systems. To check the contraction property, a condition of negativity on the Jacobian of the system has to be fulfilled. In this paper, attention is paid to results for which the negativity condition can be relaxed, i.e. the maximum eigenvalue of the Jacobian may take zero or positive values. In this issue, we present a theorem and a corollary which sufficient conditions enable to conclude when the Jacobian is not uniformly negative definite but fulfils some weaker conditions. Intended as an illustrative example, a nonlinear underwater vehicle observer, which Jacobian is not uniformly negative definite, is presented and proven to be exponentially convergent using the new criterion.
Summationtype conditions for uniform asymptotic convergence in discretetime systems: applications in identification
, 2005
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COMMANDE ET CONSTRUCTION D’OBSERVATEURS POUR DES SYSTEMES NON
"... (Directrice de thèse) À mes parents et à Iwona. « Tout est déjà dans l’air il me semble. J’ai ainsi vingt châteaux en l’air où je n’aurais ..."
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Cited by 2 (1 self)
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(Directrice de thèse) À mes parents et à Iwona. « Tout est déjà dans l’air il me semble. J’ai ainsi vingt châteaux en l’air où je n’aurais
Projet MERE INRIAINRA,
, 2007
"... Lyapunov functions for time varying systems satisfying generalized conditions of Matrosov theorem ∗ F. Mazenc, ..."
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Lyapunov functions for time varying systems satisfying generalized conditions of Matrosov theorem ∗ F. Mazenc,
unknown title
, 2003
"... Matrosov’s theorem using a family of auxiliary functions: an analysis tool to aid timevarying nonlinear control design ∗ ..."
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Matrosov’s theorem using a family of auxiliary functions: an analysis tool to aid timevarying nonlinear control design ∗
RESEARCH ARTICLE Moving Horizon Observer with Regularization for Detectable Systems without Persistence of Excitation
"... A constrained moving horizon observer is developed for nonlinear discretetime systems. The algorithm is proved to converge exponentially under a detectability assumption and the data being exciting at all time. However, in many practical estimation problems, such as combined state and parameter est ..."
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A constrained moving horizon observer is developed for nonlinear discretetime systems. The algorithm is proved to converge exponentially under a detectability assumption and the data being exciting at all time. However, in many practical estimation problems, such as combined state and parameter estimation, the data may not be exciting for every period of time. The algorithm therefore has regularization mechanisms to ensure robustness and graceful degradation of performance in cases when the data are not exciting. This includes the use of a priori estimates in the moving horizon cost function, and the use of thresholded singular value decomposition to avoid illconditioned or illposed inversion of the associated nonlinear algebraic equations that define the moving horizon cost function. The latter regularization relies on monitoring of the rank of an estimate of a Hessianlike matrix and conditions for uniform exponential convergence are given. The method is in particular useful with augmented state space models corresponding to mixed state and parameter estimation problems, or dynamics that are not asymptotically stable, as illustrated with two simulation examples.