Modeling and Identification of Linear Parameter-Varying Systems [electronic resource] /
Toth, Roland.author.
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, common in many industrial applications, than what the classical framework of Linear Time-Invariant (LTI) control can provide. However, it was also a primary 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 field with many promising applications. Unfortunately, modeling of LPV systems, especially based on measured data (which is called system identification) has seen a limited development since the birth of the framework. Currently this bottleneck of the LPV framework is halting the transfer of the LPV theory into industrial use. Without good models that fulfills the expectations of the users and without the understanding how these models correspond to the dynamics of the application, it is difficult 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 identification. It explores the missing details of the LPV system theory that have hindered the formulation of a well established identification framework.
Bibliographic Level Mode of Issuance: Monograph
Includes bibliographical references (p. [303]-314) and index.
LTI System Identification and the Role of OBFs -- LPV Systems and Representations -- LPV Equivalence Transformations -- LPV Series-Expansion Representations -- Discretization of LPV Systems -- LPV Modeling of Physical Systems -- Optimal Selection of OBFs -- LPV Identification via OBFs.
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, common in many industrial applications, than what the classical framework of Linear Time-Invariant (LTI) control can provide. However, it was also a primary 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 field with many promising applications. Unfortunately, modeling of LPV systems, especially based on measured data (which is called system identification) has seen a limited development since the birth of the framework. Currently this bottleneck of the LPV framework is halting the transfer of the LPV theory into industrial use. Without good models that fulfills the expectations of the users and without the understanding how these models correspond to the dynamics of the application, it is difficult 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 identification. It explores the missing details of the LPV system theory that have hindered the formulation of a well established identification framework.
Control engineering.
System theory.
Control and Systems Theory.
Systems Theory, Control.