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Author Rios, Jorge D., author.

Title Neural networks modeling and control : applications for unknown nonlinear delayed systems in discrete time / Jorge D. Rios, Alma Y. Alanis, Nancy Arana-Daniel, Carlos Lopez-Franco.

Publication Info. Amsterdam : Academic Press, 2019.

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Location Call No. OPAC Message Status
 Axe Elsevier ScienceDirect Ebook  Electronic Book    ---  Available
Description 1 online resource : illustrations.
text rdacontent
still image rdacontent
computer rdamedia
online resource rdacarrier
Note <p>1. Introduction 2. Mathematical preliminaries 3. Recurrent high order neural network identification of nonlinear discrete-time unknown system with time-delays 4. Neural identifier-control scheme for nonlinear discrete-time unknown system with time-delays 5. Recurrent high order neural network observer of nonlinear discrete-time unknown systems with time-delays 6. Neural observer-control scheme for nonlinear discrete-time unknown system with time-delays 7. Concluding remarks and future trends</p> <p>Appendix A. Artificial neural networks B. Linear induction motor prototype C. Differential robot prototype</p>
Description based on online resource, title from digital title page (viewed on December 21, 2020).
Summary Neural Networks Modelling and Control: Applications for Unknown Nonlinear Delayed Systems in Discrete Time focuses on modeling and control of discrete-time unknown nonlinear delayed systems under uncertainties based on Artificial Neural Networks. First, a Recurrent High Order Neural Network (RHONN) is used to identify discrete-time unknown nonlinear delayed systems under uncertainties, then a RHONN is used to design neural observers for the same class of systems. Therefore, both neural models are used to synthesize controllers for trajectory tracking based on two methodologies: sliding mode control and Inverse Optimal Neural Control. As well as considering the different neural control models and complications that are associated with them, this book also analyzes potential applications, prototypes and future trends. Provide in-depth analysis of neural control models and methodologies Presents a comprehensive review of common problems in real-life neural network systems Includes an analysis of potential applications, prototypes and future trends.
Subject Neural networks (Computer science)
Neural networks (Computer science) -- Industrial applications.
Discrete-time systems.
Discrete-time systems -- Industrial applications.
Réseaux neuronaux (Informatique)
Réseaux neuronaux (Informatique) -- Applications industrielles.
Systèmes échantillonnés.
Systèmes échantillonnés -- Applications industrielles.
Discrete-time systems
Neural networks (Computer science)
Neural networks (Computer science) -- Industrial applications
Added Author Alanis, Alma Y., author.
Arana-Daniel, Nancy, author.
Lopez-Franco, Carlos, author.
Other Form: Print version: 9780128170786
ISBN 9780128170793 (ePub ebook) :
0128170794
9780128170786 (pbk.)
Standard No. UKMGB 019576824
AU@ 000066495761

 
    
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