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State space systems with time-delays analysis, identification and applications /

State Space Systems with Time-Delays Analysis, Identification and Applications covers the modeling, identification and control of industrial applications, including system identification, parameter estimation, dynamic simulation, nonlinear control, and other emerging techniques. The book introduces...

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Bibliographic Details
Main Authors: Gu, Ya, Li, Chuanjiang (Author)
Corporate Author: ScienceDirect (Online service)
Other Authors: Zhu, Quan Min (Editor)
Format: eBook
Language:English
Published: London ; San Diego, CA : Academic Press, an imprint of Elsevier, [2023]
Series:Emerging methodologies and applications in modelling, identification and control
Subjects:
State-space methods.
Time delay systems.
Méthodes de l'espace état.
Systèmes à retard.
State-space methods
Time delay systems
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Front Cover
  • State Space Systems With Time-Delays Analysis, Identification, and Applications
  • Copyright Page
  • Contents
  • About the authors
  • Acknowledgment
  • Introduction
  • 1 An overview of each chapter
  • 1 One-unit state-delay identification
  • 1.1 Auxiliary model identification method for a unit time-delay system
  • 1.1.1 The input-output representation
  • 1.1.2 The auxiliary model-based squares algorithm
  • 1.1.3 Example
  • 1.1.4 Conclusions
  • 1.2 Parameter and state estimation algorithm for one-unit state-delay system
  • 1.2.1 The canonical state-space model for state-delay systems
  • 1.2.2 The identification model
  • 1.2.3 The parameter and state estimation algorithm
  • 1.2.4 Examples
  • 1.3 Conclusions
  • References
  • 2 D-step state-delay identification
  • 2.1 State filtering and parameter estimation for d-step state delay
  • 2.1.1 The system description and identification model
  • 2.1.2 The parameter estimation algorithm
  • 2.1.3 The state estimation algorithm
  • 2.1.4 Example
  • 2.1.5 Conclusions
  • 2.2 Identification and U-control of dual-rate state-space models with d-step state delay
  • 2.2.1 The canonical state-space model for state-delay systems
  • 2.2.2 The identification model
  • 2.2.3 The parameter and state estimation algorithm
  • 2.2.4 The state estimation algorithm
  • 2.2.5 U-model control
  • 2.2.6 Examples
  • 2.2.7 Conclusions
  • 2.3 Parameter estimation algorithm for d-step time-delay systems
  • 2.3.1 Problem description
  • 2.3.2 The identification model
  • 2.3.3 The parameter and state estimation algorithm
  • 2.3.4 Example
  • 2.3.5 Conclusions
  • 2.4 Communicative state and parameters estimation for dual-rate state-space systems with time delays
  • 2.4.1 Problem formulation
  • 2.4.2 Augmented state estimation
  • 2.4.3 Recursive parameter estimation
  • 2.4.4 Case study
  • 2.5 Conclusion
  • References.
  • 3 Multiple state-delay identification
  • 3.1 Parameter estimation and convergence for state-space model with time delay
  • 3.1.1 The system description and identification model
  • 3.1.2 The parameter estimation algorithm
  • 3.1.3 Main convergence results
  • 3.1.4 Example
  • 3.1.5 Conclusions
  • 3.2 Iterative parameter estimation for state-space model with multistate delays based on decomposition
  • 3.2.1 System description and identification model
  • 3.2.2 The hierarchical gradient-based iterative algorithm
  • 3.2.3 The hierarchical least squares-based iterative algorithm
  • 3.2.4 Example
  • 3.2.5 Conclusions
  • 3.3 Least squares-based iterative parameter estimation algorithm for multiple time delay
  • 3.3.1 The system description and input-output representation
  • 3.3.2 The identification model and parameter estimation algorithm
  • 3.3.3 Example
  • 3.3.4 Conclusions
  • 3.4 Two-stage least squares-based iterative parameter identification algorithm for time-delay systems
  • 3.4.1 The system description and input-output representation
  • 3.4.2 The two-stage least squares-based iterative algorithm
  • 3.4.3 The least squares-based iterative algorithm
  • 3.4.4 Example
  • 3.5 Conclusions
  • References
  • 4 Multivariable time-delay system identification
  • 4.1 Parameter estimation for a multivariable state space system with d-step delay
  • 4.1.1 The canonical state space model for state delay systems
  • 4.1.2 The identification model
  • 4.1.3 The parameter and state estimation algorithm
  • 4.1.4 Example
  • 4.1.5 Conclusions
  • 4.2 State filtering and parameter estimation for multivariable system
  • 4.2.1 The problem formulation
  • 4.2.2 The parameter estimation algorithm
  • 4.2.3 The state estimation algorithm
  • 4.2.4 Example
  • 4.2.5 Conclusions
  • References
  • 5 Nonlinear time-delay system identification.
  • 5.1 Parameter estimation for a Hammerstein state-space system with time delay
  • 5.1.1 The system description and input-output representation
  • 5.1.2 The stochastic gradient algorithm
  • 5.1.3 The iterative algorithms
  • 5.1.3.1 The gradient-based iterative algorithm
  • 5.1.3.2 The least squares-based iterative algorithm
  • 5.1.4 Example
  • 5.1.5 Conclusions
  • 5.2 The bias compensation-based parameter and state estimation for a nonlinear system
  • 5.2.1 The system description and identification model
  • 5.2.2 The parameter estimation algorithm
  • 5.2.3 The state estimation algorithm
  • 5.2.4 Examples
  • 5.3 Conclusion
  • Appendix
  • References
  • 6 Uncertain state delay systems identification
  • 6.1 State space model identification of multirate processes with uncertain time delay
  • 6.1.1 Problem statement
  • 6.1.2 Model identification using the EM algorithm
  • 6.1.3 Simulation study
  • 6.1.4 Conclusions
  • 6.2 Moving horizon estimation for multirate system with time-varying time delays
  • 6.2.1 Problem statement
  • 6.2.2 Moving horizon estimation
  • 6.2.2.1 MHE formulation
  • 6.2.3 Arrival cost
  • 6.2.4 Objective function
  • 6.2.4.1 Optimization procedure
  • 6.2.5 Simulation study
  • 6.2.6 Wood-Berry distillation column simulation
  • 6.2.7 Conclusions
  • References
  • Index
  • Back Cover.