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Nonlinear Pinning Control Of Complex Dynamical Networks Analysis And Applications Automation And Control Engineering 1st Edition Edgar N Sanchez

  • SKU: BELL-33354430
Nonlinear Pinning Control Of Complex Dynamical Networks Analysis And Applications Automation And Control Engineering 1st Edition Edgar N Sanchez
$ 31.00 $ 45.00 (-31%)

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Nonlinear Pinning Control Of Complex Dynamical Networks Analysis And Applications Automation And Control Engineering 1st Edition Edgar N Sanchez instant download after payment.

Publisher: CRC Press
File Extension: PDF
File size: 11.34 MB
Pages: 228
Author: Edgar N. Sanchez, Carlos J. Vega, Oscar J. Suarez, Guanrong Chen
ISBN: 9781032020877, 1032020873
Language: English
Year: 2021
Edition: 1

Product desciption

Nonlinear Pinning Control Of Complex Dynamical Networks Analysis And Applications Automation And Control Engineering 1st Edition Edgar N Sanchez by Edgar N. Sanchez, Carlos J. Vega, Oscar J. Suarez, Guanrong Chen 9781032020877, 1032020873 instant download after payment.

This book presents two nonlinear control strategies for complex dynamical networks. First, sliding-mode control is used, and then the inverse optimal control approach is employed. For both cases, model-based is considered in Chapter 3 and Chapter 5; then, Chapter 4 and Chapter 6 are based on determining a model for the unknow system using a recurrent neural network, using on-line extended Kalman filtering for learning.

The book is organized in four sections. The first one covers mathematical preliminaries, with a brief review for complex networks, and the pinning methodology. Additionally, sliding-mode control and inverse optimal control are introduced. Neural network structures are also discussed along with a description of the high-order ones. The second section presents the analysis and simulation results for sliding-mode control for identical as well as non-identical nodes. The third section describes analysis and simulation results for inverse optimal control considering identical or non-identical nodes. Finally, the last section presents applications of these schemes, using gene regulatory networks and microgrids as examples.

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