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Control and dynamic systems [electronic resource] / edited by Cornelius T. Leondes.

Contributor(s): Material type: TextTextSeries: Neural network systems, techniques and applications ; v. 7.Publication details: San Diego, Calif. : Academic Press, ©1998.Description: 1 online resource (xx, 438 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780080553900
  • 0080553907
Subject(s): Genre/Form: Additional physical formats: Print version:: Control and dynamic systems.DDC classification:
  • 006.32 22
LOC classification:
  • QA76.87 .N4774 1998eb
Online resources:
Contents:
Orthogonal functions for systems identification and control / Chaoying Zhu, Deepak Shukla, and Frank W. Paul -- Multilayer recurrent neural networks for synthesizing and tuning linear control systems via pole assignment / Jun Wang -- Direct and indirect techniques to control unknown nonlinear dynamical systems using dynamical neural networks / George A. Rovithakis and Manolis A. Christodoulou -- A receding horizon optimal tracking neurocontroller for nonlinear dynamic systems / Young-Moon Park, Myeon-Song, Choi and Kwang Y. Lee -- On-line approximators for nonlinear system identification : a unified approach / Marios M. Polycarpou -- The determination of multivariable nonlinear models for dynamic systems / S.M. Billings and S. Chen -- High-order neural network systems in the identification of dynamical systems / Elias B. Kosmatopoulos and Manolis A. Christodoulou -- Neurocontrols for systems with unknown dynamics / William A. Porter, Wie Liu, and Luis Trevino -- On-line learning neural networks for aircraft autopilot and command augmentation systems / Marcello Napolitano and Michael Kincheloe -- Nonlinear system modeling / Shaohua Tan [and others].
Summary: The book emphasizes neural network structures for achieving practical and effective systems, and provides many examples. Practitioners, researchers, and students in industrial, manufacturing, electrical, mechanical,and production engineering will find this volume a unique and comprehensive reference source for diverse application methodologies.Control and Dynamic Systems covers the important topics of highly effective Orthogonal Activation Function Based Neural Network System Architecture, multi-layer recurrent neural networks for synthesizing and implementing real-time linear control,adaptive.
Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
eBook eBook e-Library EBSCO Computers Available
Total holds: 0

Includes bibliographical references and index.

Orthogonal functions for systems identification and control / Chaoying Zhu, Deepak Shukla, and Frank W. Paul -- Multilayer recurrent neural networks for synthesizing and tuning linear control systems via pole assignment / Jun Wang -- Direct and indirect techniques to control unknown nonlinear dynamical systems using dynamical neural networks / George A. Rovithakis and Manolis A. Christodoulou -- A receding horizon optimal tracking neurocontroller for nonlinear dynamic systems / Young-Moon Park, Myeon-Song, Choi and Kwang Y. Lee -- On-line approximators for nonlinear system identification : a unified approach / Marios M. Polycarpou -- The determination of multivariable nonlinear models for dynamic systems / S.M. Billings and S. Chen -- High-order neural network systems in the identification of dynamical systems / Elias B. Kosmatopoulos and Manolis A. Christodoulou -- Neurocontrols for systems with unknown dynamics / William A. Porter, Wie Liu, and Luis Trevino -- On-line learning neural networks for aircraft autopilot and command augmentation systems / Marcello Napolitano and Michael Kincheloe -- Nonlinear system modeling / Shaohua Tan [and others].

Print version record.

The book emphasizes neural network structures for achieving practical and effective systems, and provides many examples. Practitioners, researchers, and students in industrial, manufacturing, electrical, mechanical,and production engineering will find this volume a unique and comprehensive reference source for diverse application methodologies.Control and Dynamic Systems covers the important topics of highly effective Orthogonal Activation Function Based Neural Network System Architecture, multi-layer recurrent neural networks for synthesizing and implementing real-time linear control,adaptive.

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