Download PDF by Hugues Garnier, Liuping Wang: Identification of Continuous-time Models from Sampled Data

By Hugues Garnier, Liuping Wang

ISBN-10: 1848001606

ISBN-13: 9781848001602

ISBN-10: 1848001614

ISBN-13: 9781848001619

System identity is a longtime box within the sector of process research and keep an eye on. It goals to figure out specific types for dynamical platforms in keeping with saw inputs and outputs. even if dynamical platforms within the actual global are clearly defined within the continuous-time area, so much procedure id schemes were in accordance with discrete-time versions with out challenge for the advantages of typical continuous-time version descriptions. The continuous-time nature of actual legislation, the chronic acclaim for predominantly continuous-time proportional-integral-derivative regulate and the extra direct nature of continuous-time fault analysis tools make continuous-time modeling of ongoing value.

Identification of Continuous-time types from Sampled Data brings jointly contributions from recognized specialists who current an up to date view of this energetic region of analysis and describe contemporary tools and software program instruments built during this box. they give a clean examine and new leads to parts such as:

• time and frequency area optimum statistical techniques to identification;

• parametric identity for linear, nonlinear and stochastic platforms;

• id utilizing instrumental variable, subspace and information compression methods;

• closed-loop and strong identity; and

• continuous-time modeling from non-uniformly sampled info and for structures with hold up.

The Continuous-Time procedure id (CONTSID) toolbox defined within the publication provides an summary of advancements and sensible examples during which MATLAB® may be delivered to endure within the explanation for direct time-domain identity of continuous-time systems.This survey of equipment and ends up in continuous-time approach id might be a worthwhile reference for a large viewers drawn from researchers and graduate scholars in sign processing in addition to in structures and keep an eye on. It additionally covers complete fabric appropriate for specialized graduate classes in those areas.

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Extra resources for Identification of Continuous-time Models from Sampled Data

Sample text

Process parameter estimation and self adaptive control. H. Hammond (ed), Theory of Self Adaptive Control Systems, Plenum Press, pages 118–140, 1966. 50. C. Young. An instrumental variable method for real-time identification of a noisy process. Automatica, 6:271–287, 1970. 51. C. Young. Some observations on instrumental variable methods of time-series analysis. International Journal of Control, 23:593–612, 1976. 52. C. Young. Recursive Estimation and Time-series Analysis. Springer-Verlag, Berlin, 1984.

R. Johansson, M. T. Chou. Stochastic theory of continuoustime state-space identification. IEEE Transactions on Signal Processing, 47(1):41–50, 1999. 18. E. W. Hunter. System identification of human joint dynamics. Critical Reviews in Biomedical Engineering, 18(1):55–87, 2000. 19. E. Larsson. Identification of Stochastic Continuous-time Systems. Algorithms, Irregular Sampling and Cram´er-Rao Bounds. PhD thesis, Uppsala University, Sweden, 2004. 20. S. Levadi. Parameter estimation of linear systems in the presence of noise.

Identification of Stochastic Continuous-time Systems. Algorithms, Irregular Sampling and Cram´er-Rao Bounds. PhD thesis, Uppsala University, Sweden, 2004. 20. S. Levadi. Parameter estimation of linear systems in the presence of noise. International Conference on Microwaves, Circuit Theory and Information Theory, Tokyo, Japan, 1964. 21. W. Li, H. Raghavan, and S. Shah. Subspace identification of continuous time models for process fault detection and isolation. Journal of Process Control, 13(5):407–421, 2003.

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Identification of Continuous-time Models from Sampled Data by Hugues Garnier, Liuping Wang


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