
Neural Network Control of Nonlinear Discrete-Time Systems
Jagannathan Sarangapani(Author)
CRC Press
1st Edition
Published on 24. April 2006
Book
Hardback
622 pages
978-0-8247-2677-5 (ISBN)
Description
Intelligent systems are a hallmark of modern feedback control systems. But as these systems mature, we have come to expect higher levels of performance in speed and accuracy in the face of severe nonlinearities, disturbances, unforeseen dynamics, and unstructured uncertainties. Artificial neural networks offer a combination of adaptability, parallel processing, and learning capabilities that outperform other intelligent control methods in more complex systems.
Borrowing from Biology
Examining neurocontroller design in discrete-time for the first time, Neural Network Control of Nonlinear Discrete-Time Systems presents powerful modern control techniques based on the parallelism and adaptive capabilities of biological nervous systems. At every step, the author derives rigorous stability proofs and presents simulation examples to demonstrate the concepts.
Progressive Development
After an introduction to neural networks, dynamical systems, control of nonlinear systems, and feedback linearization, the book builds systematically from actuator nonlinearities and strict feedback in nonlinear systems to nonstrict feedback, system identification, model reference adaptive control, and novel optimal control using the Hamilton-Jacobi-Bellman formulation. The author concludes by developing a framework for implementing intelligent control in actual industrial systems using embedded hardware.
Neural Network Control of Nonlinear Discrete-Time Systems fosters an understanding of neural network controllers and explains how to build them using detailed derivations, stability analysis, and computer simulations.
Borrowing from Biology
Examining neurocontroller design in discrete-time for the first time, Neural Network Control of Nonlinear Discrete-Time Systems presents powerful modern control techniques based on the parallelism and adaptive capabilities of biological nervous systems. At every step, the author derives rigorous stability proofs and presents simulation examples to demonstrate the concepts.
Progressive Development
After an introduction to neural networks, dynamical systems, control of nonlinear systems, and feedback linearization, the book builds systematically from actuator nonlinearities and strict feedback in nonlinear systems to nonstrict feedback, system identification, model reference adaptive control, and novel optimal control using the Hamilton-Jacobi-Bellman formulation. The author concludes by developing a framework for implementing intelligent control in actual industrial systems using embedded hardware.
Neural Network Control of Nonlinear Discrete-Time Systems fosters an understanding of neural network controllers and explains how to build them using detailed derivations, stability analysis, and computer simulations.
More details
Series
Language
English
Place of publication
Bosa Roca
United States
Publishing group
Taylor & Francis Inc
Target group
Professional and scholarly
Professional
Illustrations
171 s/w Abbildungen, 23 s/w Tabellen
23 Tables, black and white; 171 Illustrations, black and white
Dimensions
Height: 229 mm
Width: 152 mm
Weight
1310 gr
ISBN-13
978-0-8247-2677-5 (9780824726775)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Jagannathan Sarangapani
Neural Network Control of Nonlinear Discrete-Time Systems
E-Book
10/2018
CRC Press
€310.99
Available for download

Jagannathan Sarangapani
Neural Network Control of Nonlinear Discrete-Time Systems
E-Book
10/2018
1st Edition
CRC Press
€311.99
Available for download
Person
Sarangapani, Jagannathan
Content
Background on Neural Networks. Background and Discrete-Time Adaptive Control. Neural Network Control of Nonlinear Systems and Feedback Linearization. Neural Network Control of Uncertain Nonlinear Discrete-Time Systems with Actuator Nonlinearities. Output Feedback Control of Strict Feedback Nonlinear MIMO Discrete-Time Systems. Neural Network Control of Nonstrict Feedback Nonlinear Systems. System Identification Using Discrete-Time Neural Networks. Discrete-Time Model Reference Adaptive Control. Neural Network Control in Discrete-Time Using Hamilton-Jacobi-Bellman Formulation. Neural Network Output Feedback Controller Design and Embedded Hardware Implementation. Index.