The Experts below are selected from a list of 9765 Experts worldwide ranked by ideXlab platform

Hugues Garnier - One of the best experts on this subject based on the ideXlab platform.

  • benchmark problems for Continuous Time Model identification design aspects results and perspectives
    Automatica, 2019
    Co-Authors: Valentin Pascu, Hugues Garnier, Lennart Ljung, Alexandre Janot
    Abstract:

    The problem of estimating Continuous-Time Model parameters of linear dynamical systems using sampled Time-domain input and output data has received considerable attention over the past decades and has been approached by various methods. The research topic also bears practical importance due to both its close relation to first principles Modeling and equally to linear Model-based control design techniques, most of them carried in Continuous Time. Nonetheless, as the performance of the existing algorithms for Continuous-Time Model identification has seldom been assessed and, as thus far, it has not been considered in a comprehensive study, this practical potential of existing methods remains highly questionable. The goal of this brief paper is to bring forward a first study on this issue and to factually highlight the main aspects of interest. As such, an analysis is performed on a benchmark designed to be consistent both from a system identification viewpoint and from a control-theoretic one. It is concluded that robust initialization aspects require further research focus towards reliable algorithm development.

  • refined instrumental variable method for hammerstein wiener Continuous Time Model identification
    Iet Control Theory and Applications, 2013
    Co-Authors: Boyi Ni, Marion Gilson, Hugues Garnier
    Abstract:

    This study presents the first attempt of direct Continuous-Time Model identification using instrumental variable method for Hammerstein–Wiener systems from sampled data. Under the assumption of monotonic function for the Wiener part, the whole non-linear Model is first estimated as an augmented multiple-input single-output linear Model, from which the Model parameters are then extracted by singular value decomposition. A refined instrumental variable method is proposed to consistently identify this non-linear system acting in a coloured noisy environment. Monte Carlo simulation analysis is presented to illustrate the effectiveness of the proposed method.

  • What does Continuous-Time Model identification have to offer?
    IFAC Proceedings Volumes, 2012
    Co-Authors: Hugues Garnier, Peter C. Young
    Abstract:

    Abstract Direct identification of Continuous-Time Models from sampled data is now mature. The developed methods have proven successful in many practical applications and are available as user-friendly and computationally efficient algorithms in the CAPTAIN and CONTSID toolboxes for Matlab ™ . Surprisingly many practitioners appear unaware that such methods not only exist but may be better suited to their Modelling problems. This paper discusses and illustrates with the help of real-life data the advantages of these direct schemes to Continuous-Time Model identification.

  • Data-based Continuous-Time Modelling of dynamic systems
    2011
    Co-Authors: Hugues Garnier
    Abstract:

    Data-based Continuous-Time Model identification of Continuous-Time dynamic systems is a mature subject. In this contribution, we focus first on a refined instrumental variable method that yields parameter estimates with optimal statistical properties for hybrid Continuous-Time Box-Jenkins transfer function Models. The second part of the paper describes further recent developments of this reliable estimation technique, including its extension to handle non-uniformly sampled data situation, closed-loop and nonlinear Model identification. It also discusses how the recently developed methods are implemented in the CONTSID toolbox for Matlab and the advantages of these direct schemes to Continuous-Time Model identification.

  • Editorial special issue on Continuous-Time Model identification
    Iet Control Theory and Applications, 2011
    Co-Authors: Hugues Garnier, Torsten Söderström
    Abstract:

    International audienceThis editorial introduces the special issue on Continuous-Time Model identification and briefly presents the selected papers

Raymond B. Ridley - One of the best experts on this subject based on the ideXlab platform.

  • a new Continuous Time Model for current mode control power convertors
    IEEE Transactions on Power Electronics, 1991
    Co-Authors: Raymond B. Ridley
    Abstract:

    A current-mode control power convertor Model that is accurate at frequencies from DC to half the switching frequency is described for constant-frequency operation. Using a simple pole-zero transfer function, the Model is able to predict subharmonic oscillation without the need for discrete-Time z-transform Models. The accuracy of sampled-data Modeling is incorporated into the Model by a second-order representation of the sampled-data transfer function which is valid up to half the switching frequency. Predictions of current loop gain; control-to-output; output impedance; and audio susceptibility transfer functions were confirmed with measurements on a buck converter. The audio susceptibility of the buck converter can be nulled with the appropriate value of external ramp. The Modeling concentrates on constant-frequency pulse-width modulation (PWM) converters, but the methods can be applied to variable-frequency control and disContinuous conduction mode. >

  • A New, Continuous-Time Model For Current-Mode Control
    IEEE Transactions on Power Electronics, 1991
    Co-Authors: Raymond B. Ridley
    Abstract:

    A current-mode control power convertor Model that is accurate at frequencies from DC to half the switching frequency is described for constant-frequency operation. Using a simple pole-zero transfer function, the Model is able to predict subharmonic oscillation without the need for discrete-Time z-transform Models. The accuracy of sampled-data Modeling is incorporated into the Model by a second-order representation of the sampled-data transfer function which is valid up to half the switching frequency. Predictions of current loop gain; control-to-output; output impedance; and audio susceptibility transfer functions were confirmed with measurements on a buck converter. The audio susceptibility of the buck converter can be nulled with the appropriate value of external ramp. The Modeling concentrates on constant-frequency pulse-width modulation (PWM) converters, but the methods can be applied to variable-frequency control and disContinuous conduction mode

S.l. Shah - One of the best experts on this subject based on the ideXlab platform.

  • Continuous-Time Model identification of fractional-order Models with Time delays
    IET Control Theory & Applications, 2011
    Co-Authors: Tao Chen, Anshu Narang, S.l. Shah
    Abstract:

    Modelling of real physical systems having long memory transients and infinite dimensional structures using fractional-order dynamic Models has significantly attracted interest over the last few years. For this reason, many identification techniques both in the frequency domain and Time domain have been developed to Model these fractional-order systems. However, in many processes Time delays are also present and estimation of Time delays along with Continuous-Time fractional-order Model parameters have not been addressed anywhere. This study deals with the Continuous-Time Model identification of fractional-order system Models with Time delays. In this study, a new linear filter is introduced for simultaneous estimation of all Model parameters for commensurate fractional-order system Models with Time delays. The proposed method simultaneously estimates Time delays along with other Model parameters in an iterative manner by solving simple linear regression equations. For the case when the fractional order is unknown, we also propose a nested loop optimisation method where the Time delay along with other Model parameters are estimated iteratively in the inner loop and the fractional order is estimated in the non-linear outer loop. The applicability of the developed procedure is demonstrated by simulations on a fractional-order system Model by doing Monte Carlo simulation analysis in the presence of white noise. The proposed algorithm has also been applied to identify a process of thermal diffusion in a wall in simulation, which are characterised by fractional-order behaviour.

  • Continuous Time Model identification of fractional order Models with Time delays
    IFAC Proceedings Volumes, 2009
    Co-Authors: Anshu Narang, S.l. Shah, Tongwen Chen
    Abstract:

    Abstract This paper deals with the Continuous-Time Model identification (CMI) of fractional order systems with Time delays. In this paper, a new linear filter is introduced for simultaneous estimation of all Model parameters for commensurate fractional order systems with Time delays (CFOTDS) based on step response data. The proposed method simultaneously estimates the Time delay along with other Model parameters in an iterative manner by solving simple linear regression equations. For the case when the fractional order is unknown, we also propose a nested loop optimization method where the Time delay along with other Model parameters are estimated iteratively in the inner loop and the fractional order is estimated in the non-linear outer loop. The applicability of the developed procedure is demonstrated on two fractal systems by doing Monte Carlo simulation analysis in the presence of white noise.

Boyi Ni - One of the best experts on this subject based on the ideXlab platform.

  • refined instrumental variable method for hammerstein wiener Continuous Time Model identification
    Iet Control Theory and Applications, 2013
    Co-Authors: Boyi Ni, Marion Gilson, Hugues Garnier
    Abstract:

    This study presents the first attempt of direct Continuous-Time Model identification using instrumental variable method for Hammerstein–Wiener systems from sampled data. Under the assumption of monotonic function for the Wiener part, the whole non-linear Model is first estimated as an augmented multiple-input single-output linear Model, from which the Model parameters are then extracted by singular value decomposition. A refined instrumental variable method is proposed to consistently identify this non-linear system acting in a coloured noisy environment. Monte Carlo simulation analysis is presented to illustrate the effectiveness of the proposed method.

Marion Gilson - One of the best experts on this subject based on the ideXlab platform.

  • refined instrumental variable method for hammerstein wiener Continuous Time Model identification
    Iet Control Theory and Applications, 2013
    Co-Authors: Boyi Ni, Marion Gilson, Hugues Garnier
    Abstract:

    This study presents the first attempt of direct Continuous-Time Model identification using instrumental variable method for Hammerstein–Wiener systems from sampled data. Under the assumption of monotonic function for the Wiener part, the whole non-linear Model is first estimated as an augmented multiple-input single-output linear Model, from which the Model parameters are then extracted by singular value decomposition. A refined instrumental variable method is proposed to consistently identify this non-linear system acting in a coloured noisy environment. Monte Carlo simulation analysis is presented to illustrate the effectiveness of the proposed method.

  • an optimal iv technique for identifying Continuous Time transfer function Model of multiple input systems
    Control Engineering Practice, 2007
    Co-Authors: Hugues Garnier, Peter C. Young, Marion Gilson, E. Huselstein
    Abstract:

    An instrumental variable method for Continuous-Time Model identification is proposed for multiple input single output systems where the characteristic polynomials of the transfer functions associated with each input are not constrained to be identical. An associated Model order determination procedure is shown to be reasonably successful. Monte Carlo simulation analyses are used to demonstrate the properties and general robustness of the Model order selection and parameter estimation schemes. The results obtained to Model a winding process and an industrial binary distillation column illustrate the practical applicability of the proposed identification scheme.

  • Continuous-Time Model identification of systems operating in closed-loop
    IFAC Proceedings Volumes, 2003
    Co-Authors: Marion Gilson, Hugues Garnier
    Abstract:

    Abstract Schemes for system identification based on closed-loop experiments have attracted considerable interest in the last two decades. Most of the existing methods have been developed for discrete-Time Models. In this paper, various instrumental variable-based methods for identifying Continuous-Time Models of systems operating in closed-loop are proposed and their performances are compared on the basis of numerical simulations.