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Springer Fully Tuned RBF Neural Networks for Flight Control - Springer

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Description

Fully Tuned Radial Basis Function Neural Networks for Flight Control explores adaptive control of nonlinear systems using RBF neural networks, with specific focus on aerospace applications. This volume presents a Lyapunov synthesis approach to derive tuning rules that guarantee closed-loop system stability. Unlike conventional methods that adjust only network weights, this book delivers comprehensive tuning derivations for RBF network centers, widths, and weights, enabling more robust and effective flight control implementations. Part of The International Series on Asian Studies in Computer and Information Science, this technical resource bridges advanced neural network theory with practical flight dynamics challenges, offering researchers and engineers detailed methodologies for implementing adaptive control systems in demanding aerospace environments.

Key Features

Covers Radial Basis Function neural network design specifically optimised for nonlinear flight control systems.

Presents Lyapunov synthesis methods to derive tuning rules that guarantee stability of the closed-loop control system.

Includes tuning derivations for RBF network centers, widths, and weights rather than weights alone.

Addresses adaptive control applications with emphasis on aerospace and flight dynamics.

Published by Springer as part of The International Series on Asian Studies in Computer and Information Science.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
07 December 2010
Listed Since
06 July 2010

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