Tensor Product Model Transformation in Polytopic Model-Based Control

Book 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® 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

  1. Front Cover (1/2)
  2. Front Cover (2/2)
  3. Contents
  4. Preface
  5. Acronyms and Abbreviations
  6. Chapter 1: Introduction (1/2)
  7. Chapter 1: Introduction (2/2)
  8. Part I: Tensor Product (TP) Model Formulation
    1. Chapter 2: TP Model (1/2)
    2. Chapter 2: TP Model (2/2)
    3. Chapter 3: TP Model Transformation (1/3)
    4. Chapter 3: TP Model Transformation (2/3)
    5. Chapter 3: TP Model Transformation (3/3)
    6. Chapter 4: TP Canonical Model Form (1/4)
    7. Chapter 4: TP Canonical Model Form (2/4)
    8. Chapter 4: TP Canonical Model Form (3/4)
    9. Chapter 4: TP Canonical Model Form (4/4)
    10. Chapter 5: Approximation and Complexity Trade-Off (1/3)
    11. Chapter 5: Approximation and Complexity Trade-Off (2/3)
    12. Chapter 5: Approximation and Complexity Trade-Off (3/3)
    13. Chapter 6: TP Model Convexity Incorporation (1/4)
    14. Chapter 6: TP Model Convexity Incorporation (2/4)
    15. Chapter 6: TP Model Convexity Incorporation (3/4)
    16. Chapter 6: TP Model Convexity Incorporation (4/4)
    17. Chapter 7: Introduction to the TPtool Toolbox (1/2)
    18. Chapter 7: Introduction to the TPtool Toolbox (2/2)
    19. Chapter 8: Centralized Model Form (1/2)
    20. Chapter 8: Centralized Model Form (2/2)
    21. Chapter 9: Computational Relaxed TP Model Transformation (1/4)
    22. Chapter 9: Computational Relaxed TP Model Transformation (2/4)
    23. Chapter 9: Computational Relaxed TP Model Transformation (3/4)
    24. Chapter 9: Computational Relaxed TP Model Transformation (4/4)
  9. Part II: TP Model-Based Control System Design
    1. Chapter 10: Overview of TP Model-Based Design Strategy (1/2)
    2. Chapter 10: Overview of TP Model-Based Design Strategy (2/2)
    3. Chapter 11: LMI Theorems under the PDC Framework (1/5)
    4. Chapter 11: LMI Theorems under the PDC Framework (2/5)
    5. Chapter 11: LMI Theorems under the PDC Framework (3/5)
    6. Chapter 11: LMI Theorems under the PDC Framework (4/5)
    7. Chapter 11: LMI Theorems under the PDC Framework (5/5)
    8. Chapter 12: Convex Hull Manipulation (1/2)
    9. Chapter 12: Convex Hull Manipulation (2/2)
  10. Part III: Control Design Examples
    1. Chapter 13: Control Design with TPtool Toolbox
    2. Chapter 14: 2-D Prototypical Aeroelastic Wing Section with Structural Nonlinearity (1/5)
    3. Chapter 14: 2-D Prototypical Aeroelastic Wing Section with Structural Nonlinearity (2/5)
    4. Chapter 14: 2-D Prototypical Aeroelastic Wing Section with Structural Nonlinearity (3/5)
    5. Chapter 14: 2-D Prototypical Aeroelastic Wing Section with Structural Nonlinearity (4/5)
    6. Chapter 14: 2-D Prototypical Aeroelastic Wing Section with Structural Nonlinearity (5/5)
    7. Chapter 15: 3-D Prototypical Aeroelastic Wing Section with Structural Nonlinearity (1/3)
    8. Chapter 15: 3-D Prototypical Aeroelastic Wing Section with Structural Nonlinearity (2/3)
    9. Chapter 15: 3-D Prototypical Aeroelastic Wing Section with Structural Nonlinearity (3/3)
    10. Chapter 16: 3-DoF Helicopter with Four Propellers (1/3)
    11. Chapter 16: 3-DoF Helicopter with Four Propellers (2/3)
    12. Chapter 16: 3-DoF Helicopter with Four Propellers (3/3)
    13. Chapter 17: Heavy Vehicle Rollover Prevention Problem (1/2)
    14. Chapter 17: Heavy Vehicle Rollover Prevention Problem (2/2)
  11. References (1/3)
  12. References (2/3)
  13. References (3/3)

Product information

  • Title: Tensor Product Model Transformation in Polytopic Model-Based Control
  • Author(s): Péter Baranyi, Yeung Yam, Péter Várlaki
  • Release date: September 2018
  • Publisher(s): CRC Press
  • ISBN: 9781439818176