This book explores the missing details of the linear parameter-varying (LPV) system theory that have hindered the formulation of a well established identification framework. It covers the key issues from system theory to modeling and identification.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
This book aims to bridge the gap between Linear Parameter-Varying (LPV) modeling and control by investigating fundamental questions of modeling and identification. It explores missing details of LPV system theory that have hindered the formulation of a well established identification framework. By proposing a unified LPV system theory, based on a behavioral approach, the concepts of representations, equivalence transformations and means to compare model structures are re-established, giving a solid basis for an identification theory. It is also explored when and how first-principle nonlinear models can be efficiently converted to LPV descriptions detailing possible pitfalls. Building on well-founded system theoretical concepts, the classical LTI prediction-error framework is extended to the LPV case via the use of series-expansion representations. The book is written as a research monograph with a broad scope, trying to cover the key issues from system theory to modeling and identification. It is meant to be interesting for both researchers and engineers but also for graduate students in systems and control who would like to learn about the LPV framework.
This book explores the missing details of the linear parameter-varying (LPV) system theory that have hindered the formulation of a well established identification framework. It covers the key issues from system theory to modeling and identification.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Through the past 20 years, the framework of Linear Parameter-Varying (LPV) systems has become a promising system theoretical approach to handle the control of mildly nonlinear and especially position dependent systems which are common in mechatronic applications and in the process industry. The birth of this system class was initiated by the need of engineers to achieve better performance for nonlinear and time-varying dynamics, c- mon in many industrial applications, than what the classical framework of Linear Time-Invariant (LTI) control can provide. However, it was also a p- mary goal to preserve simplicity and 're-use' the powerful LTI results by extending them to the LPV case. The progress continued according to this philosophy and LPV control has become a well established eld with many promising applications. Unfortunately, modeling of LPV systems, especially based on measured data (which is called system identi cation) has seen a limited development sincethebirthoftheframework. Currentlythisbottleneck oftheLPVfra- work is halting the transfer of the LPV theory into industrial use. Without good models that ful ll the expectations of the users and without the und- standing how these models correspond to the dynamics of the application, it is di cult to design high performance LPV control solutions. This book aims to bridge the gap between modeling and control by investigating the fundamental questions of LPV modeling and identi cation. It explores the missing details of the LPV system theory that have hindered the formu- tion of a well established identi cation framework. 348 pp. Englisch. N° de réf. du vendeur 9783642138119
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents the state of the art of Modeling and Identification of Linear Parameter-Varying SystemsWritten by experts in the fieldA new appraoch on Modeling and Identification of Linear Parameter-Varying Systems Through the past 20 yea. N° de réf. du vendeur 5050309
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