Nonlinear Pinning Control of Complex Dynamical Networks : Analysis and Applications Paperback / softback

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.