Tensor product model transformation in polytopic model-based control
Author(s)
Bibliographic Information
Tensor product model transformation in polytopic model-based control
(Automation and control engineering series)
CRC Press/Taylor & Francis, c2014
Available at 2 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
Includes bibliographical references (217-228 p.) and index
Description and Table of Contents
Description
Tensor Product Model Transformation in Polytopic Model-Based Control offers a new perspective of control system design. Instead of relying solely on the formulation of more effective LMIs, which is the widely adopted approach in existing LMI-related studies, this cutting-edge book calls for a systematic modification and reshaping of the polytopic convex hull to achieve enhanced performance. Varying the convexity of the resulting TP canonical form is a key new feature of the approach. The book concentrates on reducing analytical derivations in the design process, echoing the recent paradigm shift on the acceptance of numerical solution as a valid form of output to control system problems. The salient features of the book include:
Presents a new HOSVD-based canonical representation for (qLPV) models that enables trade-offs between approximation accuracy and computation complexity
Supports a conceptually new control design methodology by proposing TP model transformation that offers a straightforward way of manipulating different types of convexity to appear in polytopic representation
Introduces a numerical transformation that has the advantage of readily accommodating models described by non-conventional modeling and identification approaches, such as neural networks and fuzzy rules
Presents a number of practical examples to demonstrate the application of the approach to generate control system design for complex (qLPV) systems and multiple control objectives.
The authors' approach is based on an extended version of singular value decomposition applicable to hyperdimensional tensors. Under the approach, trade-offs between approximation accuracy and computation complexity can be performed through the singular values to be retained in the process. The use of LMIs enables the incorporation of multiple performance objectives into the control design problem and assurance of a solution via convex optimization if feasible. Tensor Product Model Transformation in Polytopic Model-Based Control includes examples and incorporates MATLAB (R) Toolbox TPtool. It provides a reference guide for graduate students, researchers, engineers, and practitioners who are dealing with nonlinear systems control applications.
Table of Contents
Introduction. I Tensor Product (TP) Model Formulation. TP Model. TP Model Transformation. TP Canonical Model Form. Approximation and Complexity Trade-off. TP Model Convexity Incorporation. Introduction of the TPtool Toolbox. Centralized Model Form. Computational Relaxed TP Model Transformation. II TP Model-based Control System Design. Overview of TP Model-based Design Strategy. LMI Theorems under PDC Framework. Convex Hull Manipulation. III Control Design Examples. Control Design with TPtool Toolbox. 2-D Prototypical Aeroelastic Wing Section with Structural Nonlinearity. 3-D Prototypical Aeroelastic Wing Section with Structural Nonlinearity. 3-DoF Helicopter with Four Propellers. Heavy Vehicle Rollover Prevention Problem.
by "Nielsen BookData"