Nonlinear Pinning Control of Complex Dynamical Networks
CRC Press (Verlag)
978-1-032-02087-7 (ISBN)
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.
Edgar N. Sanchez works at CINVESTAV-IPN, Guadalajara Campus, Mexico, as a professor of electrical engineering graduate programs. Carlos J. Vega received D.Sc. in Electrical Engineering degree from the Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV-IPN), Guadalajara, Mexico in 2020. His research interests include complex networks, nonlinear control, inverse optimal control, neural networks, and power systems. Oscar J. Suarez is a Professor of engineering programs for undergraduate and graduate programs both in Colombia and Mexico. Currently, he is a Junior Research fellow of the Ministerio de Ciencia Tecnología e Innovación (Minciencias) in Colombia. Guanrong Chen has been a Chair Professor and the Founding Director of the Centre for Chaos and Complex Networks, City University of Hong Kong, Hong Kong, since 2000.
I. Analyses and Preliminaries: 1. Introduction. 2. Preliminaries. II. Sliding-Mode Control: 3. Model-Based Control. 4. Neural Model. III. Optimal Control: 5. Model- based Control. 6. Neural Model. IV. Applications: 7. Pinning Control for the p53-Mdm2 Network. 8. Secondary Control of Microgrids.
| Erscheinungsdatum | 23.08.2021 |
|---|---|
| Reihe/Serie | Automation and Control Engineering |
| Zusatzinfo | 4 Tables, black and white; 46 Line drawings, black and white; 46 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 453 g |
| Themenwelt | Technik ► Elektrotechnik / Energietechnik |
| Technik ► Umwelttechnik / Biotechnologie | |
| ISBN-10 | 1-032-02087-3 / 1032020873 |
| ISBN-13 | 978-1-032-02087-7 / 9781032020877 |
| Zustand | Neuware |
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