rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Discrete-time recurrent neural control
    sub title: analysis and applications
  name:
    name part: Sanchez, Edgar N.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Taylor & Francis
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: flu
    date issued: 2018
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource : illustrations.
  abstract: The book presents recent advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple outputs. The results that appear in each chapter include rigorous mathematical analyses, based on the Lyapunov approach, to establish its properties; in addition, for each chapter, simulation results are included to verify the successful performance of the corresponding proposed schemes. It provides solutions for the output trajectory tracking problem of unknown nonlinear systems based on sliding modes and inverse optimal control scheme--
  table of contents: Cover; Half Title; Title Page; Copyright Page; Dedication; Table of Contents; Preface; Acknowledgments; Authors; SECTION I: Analyses; Chapter 1: Introduction; 1.1 Preliminaries; 1.2 Motivation; 1.3 Objectives; 1.4 Book Structure; 1.5 Notation; 1.6 Acronyms; Chapter 2: Mathematical Preliminaries; 2.1 Optimal Control; 2.2 Lyapunov Stability; 2.3: Robust Stability Analysis; 2.3.1 Optimal Control for Disturbed Systems; 2.4 Passivity; 2.5 Discrete-time High Order Neural Networks; 2.6 The EKF Training Algorithm; 2.7 Separation Principle for Discrete-time Nonlinear Systems.
  table of contents: Chapter 3: Neural Block Control3.1 Identification; 3.2 Illustrative Example; 3.3 Neural Block Controller Design; 3.4 Applications; 3.4.1 Neural Network Identification; 3.4.2 Neural Block Controller Design; 3.4.3 Reduced Order Nonlinear Observer; 3.4.4 Simulation Results; 3.5 Conclusions; Chapter 4: Neural Optimal Control; 4.1 Inverse Optimal Control via CLF; 4.1.1 Example; 4.1.2 Inverse Optimal Control for Linear Systems; 4.2 Robust Inverse Optimal Control; 4.3 Trajectory Tracking Inverse Optimal Control; 4.3.1 Application to the Boost Converter; 4.3.1.1 Boost Converter Model.
  table of contents: 4.3.1.2 Control Synthesis4.3.1.3 Simulation Results; 4.4 CLF-based Inverse Optimal Control for a Class of Nonlinear Positive Systems; 4.5 Speed-gradient for the Inverse Optimal Control; 4.5.1 Speed-gradient Algorithm; 4.5.2 Summary of the Proposed SG Algorithm to Calculate Parameter pk; 4.5.3 SG Inverse Optimal Control; 4.5.3.1 Example; 4.5.4 Application to the Inverted Pendulum on a Cart; 4.5.4.1 Simulation Results; 4.6 Speed-gradient Algorithm for Trajectory Tracking; 4.6.1 Example; 4.7 Trajectory Tracking for Systems in Block-control Form; 4.7.1 Example; 4.8 Neural Inverse Optimal Control.
  table of contents: 4.8.1 Stabilization4.8.1.1 Example; 4.8.2 Trajectory Tracking; 4.8.2.1 Application to a Synchronous Generator; 4.8.2.2 Comparison; 4.9 Block-control Form: A Nonlinear Systems Particular Class; 4.9.1 Block Transformation; 4.9.2 Block Inverse Optimal Control; 4.10 Conclusions; SECTION II: Real-Time Applications; Chapter 5: Induction Motors; 5.1 Neural Identifier; 5.2 Discrete-time Super-twisting Observer; 5.3 Neural Sliding Modes Block Control; 5.4 Neural Inverse Optimal Control; 5.5 Implementation; 5.6 Prototype; 5.6.1 RCP System; 5.6.2 Power Electronics; 5.6.3 Signal Conditioning for ADC.
  table of contents: 5.6.4 Real-time Controller Implementation5.6.4.1 Induction Motor Inputs and Outputs; 5.6.4.2 Flux Observer; 5.6.4.3 Neural Identifier; 5.6.4.4 Serial Communication Interface; 5.6.5 Neural Sliding Mode Real-time Results; 5.6.6 Neural Inverse Optimal Control Real-time Results; 5.7 Conclusions; Chapter 6: Doubly Fed Induction Generator; 6.1 Neural Identifiers; 6.1.1 DFIG Neural Identifier; 6.1.2 DC Link Neural Identifier; 6.2 Neural Sliding Mode Block Control; 6.2.1 DFIG Controller; 6.2.1.1 Simulation Results; 6.2.2 DC Link Controller; 6.2.2.1 Simulation Results.
  note: Edgar N. Sánchez.
  note: "A CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa plc."
  note: Includes bibliographical references and index.
  subject:
    topic: Automatic control
    topic: Data processing
  subject:
    topic: Discrete-time systems
  subject:
    topic: Neural networks (Computer science)
  subject:
    topic: Nonlinear control theory
  subject:
    topic: Neural Networks, Computer
  subject:
    topic: Commande automatique
    topic: Informatique
  subject:
    topic: Systèmes échantillonnés
  subject:
    topic: Réseaux neuronaux (Informatique)
  subject:
    topic: Commande non linéaire
  subject:
    topic: TECHNOLOGY & ENGINEERING
    topic: Engineering (General)
  subject:
    topic: TECHNOLOGY
    topic: Electricity
  subject:
    topic: TECHNOLOGY
    topic: Electronics
    topic: General
  subject:
    topic: Automatic control
    topic: Data processing
  subject:
    topic: Discrete-time systems
  subject:
    topic: Neural networks (Computer science)
  subject:
    topic: Nonlinear control theory
  classification: TJ213
  classification: 629.8/9563201183
  related item:
    title info:
      title: Discrete-time recurrent neural control
    origin info:
      publisher: Boca Raton, FL : CRC Press/Taylor & Francis Group, 2018.
    identifier: (DLC) 2018017837
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  record info:
    record content source: DLC
    record creation date: 180416
    record change date: 20241108165705.3
    record identifier: in00005522523
    language of cataloging:
      language term: eng