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Stability analysis and controller de...

Mayr, Christian.

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Stability analysis and controller design of local model networks

Record Type:	Electronic resources : Monograph/item
Title/Author:	Stability analysis and controller design of local model networks/ by Christian Mayr.
Author:	Mayr, Christian.
Published:	Wiesbaden :Springer Fachmedien Wiesbaden : : 2021.,
Description:	xxiii, 111 p. :ill., digital ;24 cm.
[NT 15003449]:	Dynamic Local Model Networks -- Open Loop Stability Analysis -- Closed-Loop Stability Analysis and Controller Design -- PID Controller Design.
Contained By:	Springer Nature eBook
Subject:	Stability. -
Online resource:	https://doi.org/10.1007/978-3-658-34008-7
ISBN:	9783658340087

Stability analysis and controller design of local model networks
Mayr, Christian.

Stability analysis and controller design of local model networks[electronic resource] /by Christian Mayr. - Wiesbaden :Springer Fachmedien Wiesbaden :2021. - xxiii, 111 p. :ill., digital ;24 cm.

Dynamic Local Model Networks -- Open Loop Stability Analysis -- Closed-Loop Stability Analysis and Controller Design -- PID Controller Design.

This book treats various methods for stability analysis and controller design of local model networks (LMNs) LMNs have proved to be a powerful tool in nonlinear dynamic system identification. Their system architecture is more suitable for controller design compared to alternative approximation methods. The main advantage is that linear controller design methods can be, at least locally, applied and combined with nonlinear optimization to calibrate stable state feedback as well as PID controller. The calibration of stable state-feedback controllers is based on the closed loop stability analysis methods. Here, global LMIs (Linear Matrix Inequalities) can be derived and numerically solved. For LMN based nonlinear PID controllers deriving global LMIs is not possible. Thus, two approaches are treated in this book. The first approach works iteratively to get LMIs in each iteration step. The second approach uses a genetic algorithm to determine the PID controller parameters where for each individual the stability is checked. It allows simultaneous enhancement of (competing) optimization criteria. About the author Christian Mayr received the M.S. degree in mechanical engineering, the Ph.D. degree in technical sciences from TU Wien, Vienna, Austria, in 2009 and 2013, respectively. Since 2013 he is with AVL List GmbH, Graz, Austria. First as Development Engineer, from 2017 as Project Manager, in 2020 as Team Leader and since 2021 Department Manager for Virtualization Application.

ISBN: 9783658340087

Standard No.: 10.1007/978-3-658-34008-7doiSubjects--Topical Terms:

544228
Stability.

LC Class. No.: QA871 / .M39 2021

Dewey Class. No.: 515.392

Stability analysis and controller design of local model networks
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505 0 $a Dynamic Local Model Networks -- Open Loop Stability Analysis -- Closed-Loop Stability Analysis and Controller Design -- PID Controller Design.
520 $a This book treats various methods for stability analysis and controller design of local model networks (LMNs) LMNs have proved to be a powerful tool in nonlinear dynamic system identification. Their system architecture is more suitable for controller design compared to alternative approximation methods. The main advantage is that linear controller design methods can be, at least locally, applied and combined with nonlinear optimization to calibrate stable state feedback as well as PID controller. The calibration of stable state-feedback controllers is based on the closed loop stability analysis methods. Here, global LMIs (Linear Matrix Inequalities) can be derived and numerically solved. For LMN based nonlinear PID controllers deriving global LMIs is not possible. Thus, two approaches are treated in this book. The first approach works iteratively to get LMIs in each iteration step. The second approach uses a genetic algorithm to determine the PID controller parameters where for each individual the stability is checked. It allows simultaneous enhancement of (competing) optimization criteria. About the author Christian Mayr received the M.S. degree in mechanical engineering, the Ph.D. degree in technical sciences from TU Wien, Vienna, Austria, in 2009 and 2013, respectively. Since 2013 he is with AVL List GmbH, Graz, Austria. First as Development Engineer, from 2017 as Project Manager, in 2020 as Team Leader and since 2021 Department Manager for Virtualization Application.
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