Adaptive Control with Recurrent High-order Neural Networks
Subtitle: Theory and Industrial Applications
By: by George A. Rovithakis, Manolis A. Christodoulou
Contributors: Christodoulou, Manolis A.
Series: Advances in Industrial Control; Advances in industrial control
Publisher: Springer London
Published: 2000
Place of publication: London
Language: eng
Format: [electronic resource] :
Number of pages: 196
ISBN-13: 9781447112013; 9781447107859
Subjects: Engineering; Computer simulation; Physics; Computer science
Description: The primary purpose of this book is to present a set of techniques which allow the design of controllers able to guarantee stability, convergence and robustness for dynamical systems with unknown nonlinearities and of manufacturing systems. To compensate for the significant amount of uncertainty in system structure, a neural network model developed recently, namely the Recurrent High Order Neural Network (RHONN), is employed. Real applications are provided with illustrations and tables for clarification; the book contains material on: - RHONN structure and approximation capabilities - indirect adaptive control - direct adaptive control - scheduling for manufacturing systems - test case for scheduling using RHONNs. The book is primarily intended for industrial and institutional practitioners but should be of significant interest to undergraduate and graduate students and academic scientists working with neural networks and their applications in engineering.
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Mode of access: World Wide Web.
Table of contents: title: Introduction; title: RHONN Structure and Approximation Capabilities; title: Indirect Adaptive Control; title: Direct Adaptive Control; title: Manufacturing Sytems Scheduling; title: Scheduling Using RHONNs: A Test Case.