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.
| Autorius: | Edgar N. Sanchez, Carlos J. Vega, Oscar J. Suarez, |
| Leidėjas: | CRC Press |
| Išleidimo metai: | 2021 |
| Knygos puslapių skaičius: | 230 |
| ISBN-10: | 1032020873 |
| ISBN-13: | 9781032020877 |
| Formatas: | Knyga kietu viršeliu |
| Kalba: | Anglų |
| Žanras: | Electrical engineering |
Parašykite atsiliepimą apie „Nonlinear Pinning Control of Complex Dynamical Networks: Analysis and Applications“
