Model-Based Control of Networked Systems
β Scribed by Eloy Garcia, Panos J. Antsaklis, Luis A. Montestruque (auth.)
- Publisher
- BirkhΓ€user Basel
- Year
- 2014
- Tongue
- English
- Leaves
- 387
- Series
- Systems & Control: Foundations & Applications
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This monograph introduces a class of networked control systems (NCS) called model-based networked control systems (MB-NCS) and presents various architectures and control strategies designed to improve the performance of NCS. The overall performance of NCS considers the appropriate use of network resources, particularly network bandwidth, in conjunction with the desired response of the system being controlled.
The book begins with a detailed description of the basic MB-NCS architecture that provides stability conditions in terms of state feedback updates. It also covers typical problems in NCS such as network delays, network scheduling, and data quantization, as well as more general control problems such as output feedback control, nonlinear systems stabilization, and tracking control.
Key features and topics include:
- Time-triggered and event-triggered feedback updates
- Stabilization of uncertain systems subject to time delays, quantization, and extended absence of feedback
- Optimal control analysis and design of model-based networked systems
- Parameter identification and adaptive stabilization of systems controlled over networks
- The MB-NCS approach to decentralized control of distributed systems
Model-Based Control of Networked Systems will appeal to researchers, practitioners, and graduate students interested in the control of networked systems, distributed systems, and systems with limited feedback.
β¦ Table of Contents
Front Matter....Pages i-xvi
Introduction....Pages 1-16
Front Matter....Pages 17-17
Model-Based Control Systems: Stability....Pages 19-53
Model-Based Control Systems: Output Feedback and Delays....Pages 55-89
Model-Based Control Systems with Intermittent Feedback....Pages 91-114
Time-Varying and Stochastic Feedback Updates....Pages 115-133
Event-Triggered Feedback Updates....Pages 135-157
Model-Based Nonlinear Control Systems....Pages 159-186
Quantization Analysis and Design....Pages 187-213
Front Matter....Pages 215-215
Optimal Control of Model-Based Event-Triggered Systems....Pages 217-231
Performance Analysis Using Lifting Techniques....Pages 233-252
Reference Input Tracking....Pages 253-275
Adaptive Stabilization of Networked Control Systems....Pages 277-307
Multirate Systems....Pages 309-325
Distributed Control Systems....Pages 327-352
Back Matter....Pages 353-382
β¦ Subjects
Systems Theory, Control
π SIMILAR VOLUMES
<p><P>The paradigm of complexity is pervading both science and engineering, leading to the emergence of novel approaches oriented at the development of a systemic view of the phenomena under study; the definition of powerful tools for modelling, estimation, and control; and the cross-fertilization o
<div>This monograph provides a comprehensive exploration of new tools for modelling, analysis, and control of networked dynamical systems. Expanding on the authorsβ previous work, this volume highlights how local exchange of information and cooperation among neighboring agents can lead to emergent g
<div>This monograph provides a comprehensive exploration of new tools for modelling, analysis, and control of networked dynamical systems. Expanding on the authorsβ previous work, this volume highlights how local exchange of information and cooperation among neighboring agents can lead to emergent g
<span>This book is inspired by the development of distributed model predictive control of networked systems to save computation and communication sources. The significant new contribution is to show how to design efficient DMPCs that can be coordinated asynchronously with the increasing effectivenes
<div>The focus of this book is the application of artificial neural networks in uncertain dynamical systems. It explains how to use neural networks in concert with adaptive techniques for system identification, state estimation, and control problems. The authors begin with a brief historical overvie