Data-Driven Modeling, Filtering and Control

Methods and Applications
Herausgeber: Novara, Carlo; Formentin, Simone

• Gebundenes Buch

Produktbeschreibung

Using important examples, this book showcases the potential of the latest data-based and data-driven methodologies for filter and control design. It discusses the most important classes of dynamic systems, along with the statistical and set membership analysis and design frameworks.

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Produktdetails

• Verlag: Institution of Engineering & Technology
• Seitenzahl: 304
• Erscheinungstermin: 4. September 2019
• Englisch
• Abmessung: 239mm x 163mm x 18mm
• Gewicht: 635g
• ISBN-13: 9781785617126
• ISBN-10: 1785617125
• Artikelnr.: 54980742

Inhaltsangabe

1. Chapter 1: Introduction
2. Part I: Data-driven modeling
* Chapter 2: A kernel-based approach to supervised nonparametric
identification of Wiener systems
* Chapter 3: Identification of a quasi-LPV model for wing-flutter
analysis using machine-learning techniques
* Chapter 4: Experimental modeling of a web-winding machine: LPV
approaches
* Chapter 5: In situ identification of electrochemical impedance
spectra for Li-ion batteries
3. Part II: Data-driven filtering and control
* Chapter 6: Dynamic measurement
* Chapter 7: Multivariable iterative learning control: analysis and
designs for engineering applications
* Chapter 8: Algorithms for data-driven H∞-norm estimation
* Chapter 9: A comparative study of VRFT and set-membership data-driven
controller design techniques: active suspension tuning case
* Chapter 10: Relative accuracy of two methods for approximating
observed Fisher information
* Chapter 11: A hierarchical approach to data-driven LPV control design
of constrained systems
* Chapter 12: Set membership fault detection for nonlinear dynamic
systems
* Chapter 13: Robust data-driven control of systems with nonlinear
distortions