1. Introduction to control-oriented modelling / Marco Lovera; 2. Object-oriented modelling and simulation of physical systems / Francesco Casella; 3. Projection-based model reduction techniques / Pierre Vuillemin, Charles Poussot-Vassal and Daniel Alazard; 4. Integrated modelling and parameter estimation: an LFR-Modelica approach / Marco Lovera and Francesco Casella; 5. Identification for robust control of complex systems: algorithm and motion application / Tom Oomen and Maarten Steinbuch.
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11. Control-oriented aeroelastic BizJet low-order LFT modeling / Charles Poussot-Vassal, Clement Roos, Pierre Vuillemin, Olivier Cantinaud and Jean-Patrick Lacoste12. Active vibration control using subspace predictive control / Gijs van der Veen, Jan-Willem van Wingerden and Michel Verhaegen; 13. Rotorcraft system identification: an integrated time-frequency-domain approach / Marco Bergamasco and Marco Lovera; 14. Parameter identification of a reduced order LFT model of anaerobic digestion / Alessandro Della Bona, Gianni Ferretti, Elena Ficara and Francesca Malpei.
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15. Modeling and parameter identification of a brake-by-wire actuator for racing motorcycles / Matteo Corno, Fabio Todeschini, Giulio Panzani and Sergio M. Savaresi16. LPV modeling and identification of a 2-DOF flexible robotic arm from local experiments using an H∞-based glocal approach / Daniel Vizer, Guillaume Mercère, Edouard Laroche and Olivier Prot; Index.
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6. Subspace-based multi-step predictors for predictive control / Marzia Cescon and Rolf Johansson7. Closed-loop subspace predictive control / Gijs van der Veen, Jan-Willem van Wingerden and Michel Verhaegen; 8. Structured nonlinear system identification / Tyrone Vincent, Kameshwar Poolla and Carlo Novara; 9. Linear fractional LPV model identification from local experiments using an H∞-based glocal approach / Daniel Vizer, Guillaume Mercère, Edouard Laroche and Olivier Prot; 10. Object-oriented modelling of spacecraft dynamics: tools and case studies / Marco Lovera and Francesco Casella.
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SUMMARY OR ABSTRACT
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The process of developing control-oriented mathematical models of physical systems is a complex task, which in general implies a careful combination of prior knowledge about the physics of the system under study with information coming from experimental data. This book presents state of the art methods and tools available within the systems and control literature to support control oriented modelling activities and to illustrate their usefulness by means of a number of case studies and applications.