| Title | : | Nonlinear Pinning Control of Complex Dynamical Networks |
|---|---|---|
| Author | : | Edgar N. Sanchez, Carlos J. Vega, Oscar J. Suarez & Guan-rong Chen |
| Release | : | 2021-08-19 |
| Kind | : | ebook |
| Genre | : | Electrical Engineering, Books, Professional & Technical, Engineering |
| Size | : | 5078651 |
| 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. |
