Nonlinear Pinning Control of Complex Dynamical Networks - Analysis and Applications

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.

General

Imprint:	Taylor & Francis
Country of origin:	United Kingdom
Series:	Automation and Control Engineering
Release date:	September 2023
First published:	2022
Authors:	Edgar N. Sanchez • Carlos J. Vega • Oscar J. Suarez • Guanrong Chen
Dimensions:	234 x 156mm (L x W)
Pages:	202
ISBN-13:	978-1-03-202093-8
Categories:	Books
LSN:	1-03-202093-8
Barcode:	9781032020938

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