Nonlinear Pinning Control of Complex Dynamical Networks

<p>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.</p><p>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. </p>