Control-oriented Modelling and Identification: Theory and practice (Control, Robotics and Sensors)

Control-oriented Modelling and Identification: Theory and practice (Control, Robotics and Sensors)

By: Marco Lovera (editor)Hardback

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Description

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.

About Author

Marco Lovera is Professor of Automatic Control at the Dipartimento di Elettronica e Informazione of the Politecnico di Milano, Italy. His research interests include system identification, spacecraft attitude and orbit control, and advanced active control applications. He is the author of more than 150 scientific publications in these areas. Professor Lovera is currently associate editor of Automatica and IEEE Transactions on Control Systems Technology and is on the editorial board of IET Control Theory and Applications and IEEE Control Systems Magazine. He is a member of the IFAC Technical Committees on Aerospace and on Control Design, and of the IEEE Control Systems Society Technical Committee on System Identification and Adaptive Control.

Contents

Chapter 1: Introduction to control-oriented modelling Chapter 2: Object-oriented modelling and simulation of physical systems Chapter 3: Projection-based model reduction techniques Chapter 4: Integrated modelling and parameter estimation: an LFR - Modelica approach Chapter 5: Identification for robust control of complex systems: algorithm and motion application Chapter 6: Subspace-based multi-step predictors for predictive control Chapter 7: Closed-loop subspace predictive control Chapter 8: Structured nonlinear system identification Chapter 9: Linear fractional LPV model identification from local experiments using an H -based glocal approach Chapter 10: Object-oriented modelling of spacecraft dynamics: tools and case studies Chapter 11: Control-oriented aeroelastic BizJet low-order LFT modeling Chapter 12: Active vibration control using subspace predictive control Chapter 13: Rotorcraft system identification: an integrated time - frequency-domain approach Chapter 14: Parameter identification of a reduced order LFT model of anaerobic digestion Chapter 15: Modeling and parameter identification of a brake-by-wire actuator for racing motorcycles Chapter 16: LPV modeling and identification of a 2-DOF flexible robotic arm from local experiments using an H -based glocal approach

Product Details

  • ISBN13: 9781849196147
  • Format: Hardback
  • Number Of Pages: 408
  • ID: 9781849196147
  • ISBN10: 1849196141

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