Control-oriented Modelling and Identification : Theory and practice. – Primera edición

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Control-oriented Modelling and Identification : Theory and practice. – Primera edición

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Lovera, Marco (Editor)

This comprehensive book covers the state-of-the-art in control-oriented modelling and identification techniques. With contributions from leading researchers in the subject, Control-oriented Modelling and Identification: Theory and practice covers the main methods and tools available to develop advanced mathematical models suitable for control system design, including: object-oriented modelling and simulation; projection-based model reduction techniques; integrated modelling and parameter estimation; identification for robust control of complex systems; subspace-based multi-step predictors for predictive control; closed-loop subspace predictive control; structured nonlinear system identification; and linear fractional LPV model identification from local experiments using an H1-based glocal approach.

This book also takes a practical look at a variety of applications of advanced modelling and identification techniques covering spacecraft dynamics, vibration control, rotorcrafts, models of anaerobic digestion, a brake-by-wire racing motorcycle actuator, and robotic arms.

Contenido:

1. Introduction to control-oriented modelling.

2. Object-oriented modelling and simulation of physical systems.

3. Projection-based model reduction techniques.

4. Integrated modelling and parameter estimation: an LFR. Modelica approach.

5. Identification for robust control of complex systems: algorithm and motion application.

6. Subspace-based multi-step predictors for predictive control.

7. Closed-loop subspace predictive control.

8. Structured nonlinear system identification.

9. Linear fractional LPV model identification from local experiments using an H -based glocal approach.

10. Object-oriented modelling of spacecraft dynamics: tools and case studies.

11. Control-oriented aeroelastic BizJet low-order LFT modeling.

12. Active vibration control using subspace predictive control.

13. Rotorcraft system identification: an integrated time- frequency-domain approach.

14. Parameter identification of a reduced order LFT model of anaerobic digestion.

15. Modeling and parameter identification of a brake-by-wire actuator for racing motorcycles.

16. LPV modeling and identification of a 2-DOF flexible robotic arm from local experiments using an H -based glocal approach.

Incluye bibliografía al final de cada capítulo
CREDITOS (Texto): Carlo Novara, Charles Poussot-Vassal, Clement Roos, Daniel Alazard, Daniel Vizer, Edouard Laroche, Francesco Casella, Gijs van der Veen, Guillaume Mercère, Jan-Willem vanWingerden, Jean-Patrick Lacoste, Kameshwar Poolla, Marco Bergamasco, Marzia Cescon,
Michel Verhaegen, Olivier Cantinaud, Olivier Prot, Pierre Vuillemin, Pierre Vuillemin, Rolf Johansson,
Tom Oomenand Maarten Steinbuch, TyroneVincent.

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