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Data-Driven, Nonparametric, Adaptive Control Theory

Data-Driven, Nonparametric, Adaptive Control Theory introduces a novel approach to the control of deterministic, nonlinear ordinary differential equations affected by uncertainties. The methods proposed enforce satisfactory trajectory tracking despite functional uncertainties in the plant model. The...

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Bibliographic Details
Main Authors: Kurdila, Andrew J. (Author), L'Afflitto, Andrea (Author), Burns, John A. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Edition:1st ed. 2025.
Series:Lecture Notes in Control and Information Sciences, 495
Subjects:
System theory.
Control theory.
Control engineering.
Functional analysis.
Systems Theory, Control.
Control and Systems Theory.
Functional Analysis.
Online Access:https://doi.org/10.1007/978-3-031-78003-5
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Table of Contents:
  • Chapter 1. Introduction
  • Chapter 2. Elements of Real and Functional Analysis
  • Chapter 3. Elements of Native Space Theory
  • Chapter 4. Elements of Dynamical Systems Theory
  • Chapter 5. Native Space Embedding Control Methods
  • Chapter 6. Data-Driven Methods and Adaptive Control: Deterministic Analysis
  • Chapter 7. Data-Driven Methods and Adaptive Control: Stochastic Analysis
  • Chapter 8. Conclusion
  • Appendix.

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