Robust and Adaptive Model Predictive Control of Nonlinear Systems (IET Control, Robotics and Sensors)

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9781849195522: Robust and Adaptive Model Predictive Control of Nonlinear Systems (IET Control, Robotics and Sensors)

This book offers a novel approach to adaptive control and provides a sound theoretical background to designing robust adaptive control systems with guaranteed transient performance. It focuses on the more typical role of adaptation as a means of coping with uncertainties in the system model.

Topics covered include an introduction to the subject; a minimally conservative perspective; an eye towards computational simplicity; estimation in adaptive control; performance improvement in adaptive control; and robust adaptive model predictive control for systems with exogeneous disturbances. This is essential reading for academics and advanced students working in control theory and applications.

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About the Author:

Veronica Adetola

Darryl DeHaan

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Martin Guay; Veronica Adetola; Darryl DeHaan
ISBN 10: 1849195528 ISBN 13: 9781849195522
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Martin Guay, Veronica Adetola, Darryl DeHaan
Published by Institution of Engineering and Technology, United Kingdom (2016)
ISBN 10: 1849195528 ISBN 13: 9781849195522
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Book Description Institution of Engineering and Technology, United Kingdom, 2016. Hardback. Book Condition: New. Language: English . Brand New Book. Most physical systems possess parametric uncertainties or unmeasurable parameters and, since parametric uncertainty may degrade the performance of model predictive control (MPC), mechanisms to update the unknown or uncertain parameters are desirable in application. One possibility is to apply adaptive extensions of MPC in which parameter estimation and control are performed online. This book proposes such an approach, with a design methodology for adaptive robust nonlinear MPC (NMPC) systems in the presence of disturbances and parametric uncertainties. One of the key concepts pursued is the concept of set-based adaptive parameter estimation, which provides a mechanism to estimate the unknown parameters as well as an estimate of the parameter uncertainty set. The knowledge of non-conservative uncertain set estimates is exploited in the design of robust adaptive NMPC algorithms that guarantee robustness of the NMPC system to parameter uncertainty. Topics covered include: a review of nonlinear MPC; extensions for performance improvement; introduction to adaptive robust MPC; computational aspects of robust adaptive MPC; finite-time parameter estimation in adaptive control; performance improvement in adaptive control; adaptive MPC for constrained nonlinear systems; adaptive MPC with disturbance attenuation; robust adaptive economic MPC; setbased estimation in discrete-time systems; and robust adaptive MPC for discrete-time systems. Bookseller Inventory # AAZ9781849195522

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Guay, Martin
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Martin Guay, Veronica Adetola, Darryl DeHaan
Published by Institution of Engineering and Technology, United Kingdom (2016)
ISBN 10: 1849195528 ISBN 13: 9781849195522
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Book Description Institution of Engineering and Technology, United Kingdom, 2016. Hardback. Book Condition: New. Language: English . Brand New Book. Most physical systems possess parametric uncertainties or unmeasurable parameters and, since parametric uncertainty may degrade the performance of model predictive control (MPC), mechanisms to update the unknown or uncertain parameters are desirable in application. One possibility is to apply adaptive extensions of MPC in which parameter estimation and control are performed online. This book proposes such an approach, with a design methodology for adaptive robust nonlinear MPC (NMPC) systems in the presence of disturbances and parametric uncertainties. One of the key concepts pursued is the concept of set-based adaptive parameter estimation, which provides a mechanism to estimate the unknown parameters as well as an estimate of the parameter uncertainty set. The knowledge of non-conservative uncertain set estimates is exploited in the design of robust adaptive NMPC algorithms that guarantee robustness of the NMPC system to parameter uncertainty. Topics covered include: a review of nonlinear MPC; extensions for performance improvement; introduction to adaptive robust MPC; computational aspects of robust adaptive MPC; finite-time parameter estimation in adaptive control; performance improvement in adaptive control; adaptive MPC for constrained nonlinear systems; adaptive MPC with disturbance attenuation; robust adaptive economic MPC; setbased estimation in discrete-time systems; and robust adaptive MPC for discrete-time systems. Bookseller Inventory # AAZ9781849195522

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Guay, Martin (Professor, Queens University, Faculty of Engineering and Applied Science, Canada)
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GUAY, MARTIN
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ISBN 10: 1849195528 ISBN 13: 9781849195522
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Book Description INST/ENGINEERING & TECHNOLOGY, 2016. Book Condition: New. This book offers a novel approach to adaptive control and provides a sound theoretical background to designing robust adaptive control systems with guaranteed transient performance. It focuses on the more typical role of adaptation as a means of coping with uncertainties in the system model. Series: Control, Robotics and Sensors. Num Pages: 250 pages. BIC Classification: TJFM. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 166 x 245 x 19. Weight in Grams: 560. . 2016. Hardcover. . . . . . Bookseller Inventory # V9781849195522

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Book Description Hardback. Book Condition: New. Not Signed; Most physical systems possess parametric uncertainties or unmeasurable parameters and, since parametric uncertainty may degrade the performance of model predictive control (MPC), mechanisms to update the unknown or uncertain parameters are desirable in application. One possibility is to apply adapti. book. Bookseller Inventory # ria9781849195522_rkm

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Book Description INST/ENGINEERING & TECHNOLOGY. Book Condition: New. This book offers a novel approach to adaptive control and provides a sound theoretical background to designing robust adaptive control systems with guaranteed transient performance. It focuses on the more typical role of adaptation as a means of coping with uncertainties in the system model. Series: Control, Robotics and Sensors. Num Pages: 250 pages. BIC Classification: TJFM. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 166 x 245 x 19. Weight in Grams: 560. . 2016. Hardcover. . . . . Books ship from the US and Ireland. Bookseller Inventory # V9781849195522

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