Electronic Resource

Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems

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Penilaian

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The focus of this book is the application of artificial neural networks in uncertain dynamical systems. It explains how to use neural networks in concert with adaptive techniques for system identification, state estimation, and control problems. The authors begin with a brief historical overview of adaptive control, followed by a review of mathematical preliminaries. In the subsequent chapters, they present several neural network-based control schemes. Each chapter starts with a concise introduction to the problem under study, and a neural network-based control strategy is designed for the simplest case scenario. After these designs are discussed, different practical limitations (i.e., saturation constraints and unavailability of all system states) are gradually added, and other control schemes are developed based on the primary scenario. Through these exercises, the authors present structures that not only provide mathematical tools for navigating control problems, but also supply solutions that are pertinent to real-life systems.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2208000024	EB0003224	621.321 Esf n	Central Library (digilib.unsri.ac.id)	Available

Detail Information

Series Title

-

Call Number

621.321 Esf n

Publisher

Switzerland : Springer Cham., 2021

Collation

xxiii, 163

Language

English

ISBN/ISSN

978-3-030-73136-6

Classification

621.321

Content Type

Ebook

Media Type

other

Carrier Type

-

Edition

-

Subject(s)

Electrical Engineering
Artificial intelligence
Power Electronics--Data processing

Specific Detail Info

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Statement of Responsibility

NO

Other version/related

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