Nonlinear Control of Dynamic Networks

Nonlinear Control of Dynamic Networks
Author :
Publisher : CRC Press
Total Pages : 344
Release :
ISBN-10 : 9781466584600
ISBN-13 : 1466584602
Rating : 4/5 (602 Downloads)

Book Synopsis Nonlinear Control of Dynamic Networks by : Tengfei Liu

Download or read book Nonlinear Control of Dynamic Networks written by Tengfei Liu and published by CRC Press. This book was released on 2018-09-03 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Significant progress has been made on nonlinear control systems in the past two decades. However, many of the existing nonlinear control methods cannot be readily used to cope with communication and networking issues without nontrivial modifications. For example, small quantization errors may cause the performance of a "well-designed" nonlinear control system to deteriorate. Motivated by the need for new tools to solve complex problems resulting from smart power grids, biological processes, distributed computing networks, transportation networks, robotic systems, and other cutting-edge control applications, Nonlinear Control of Dynamic Networks tackles newly arising theoretical and real-world challenges for stability analysis and control design, including nonlinearity, dimensionality, uncertainty, and information constraints as well as behaviors stemming from quantization, data-sampling, and impulses. Delivering a systematic review of the nonlinear small-gain theorems, the text: Supplies novel cyclic-small-gain theorems for large-scale nonlinear dynamic networks Offers a cyclic-small-gain framework for nonlinear control with static or dynamic quantization Contains a combination of cyclic-small-gain and set-valued map designs for robust control of nonlinear uncertain systems subject to sensor noise Presents a cyclic-small-gain result in directed graphs and distributed control of nonlinear multi-agent systems with fixed or dynamically changing topology Based on the authors’ recent research, Nonlinear Control of Dynamic Networks provides a unified framework for robust, quantized, and distributed control under information constraints. Suggesting avenues for further exploration, the book encourages readers to take into consideration more communication and networking issues in control designs to better handle the arising challenges.


Nonlinear Control of Dynamic Networks Related Books

Nonlinear Control of Dynamic Networks
Language: en
Pages: 344
Authors: Tengfei Liu
Categories: Technology & Engineering
Type: BOOK - Published: 2018-09-03 - Publisher: CRC Press

GET EBOOK

Significant progress has been made on nonlinear control systems in the past two decades. However, many of the existing nonlinear control methods cannot be readi
Nonlinear Control of Dynamic Networks
Language: en
Pages: 347
Authors: Tengfei Liu
Categories: Technology & Engineering
Type: BOOK - Published: 2014-04-07 - Publisher: CRC Press

GET EBOOK

Significant progress has been made on nonlinear control systems in the past two decades. However, many of the existing nonlinear control methods cannot be readi
Differential Neural Networks for Robust Nonlinear Control
Language: en
Pages: 455
Authors: Alexander S. Poznyak
Categories: Computers
Type: BOOK - Published: 2001 - Publisher: World Scientific

GET EBOOK

This book deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification
Self-Organized Biological Dynamics and Nonlinear Control
Language: en
Pages: 444
Authors: Jan Walleczek
Categories: Science
Type: BOOK - Published: 2006-04-20 - Publisher: Cambridge University Press

GET EBOOK

The growing impact of nonlinear science on biology and medicine is fundamentally changing our view of living organisms and disease processes. This book introduc
Nonlinear Dynamical Control Systems
Language: en
Pages: 427
Authors: Henk Nijmeijer
Categories: Technology & Engineering
Type: BOOK - Published: 2013-03-14 - Publisher: Springer Science & Business Media

GET EBOOK

This volume deals with controllability and observability properties of nonlinear systems, as well as various ways to obtain input-output representations. The em