Last edited by Makora
Wednesday, July 29, 2020 | History

1 edition of Networked and Distributed Predictive Control found in the catalog.

Networked and Distributed Predictive Control

Panagiotis D. Christofides

Networked and Distributed Predictive Control

Methods and Nonlinear Process Network Applications

by Panagiotis D. Christofides

  • 103 Want to read
  • 11 Currently reading

Published by Springer-Verlag London Limited in London .
Written in English

    Subjects:
  • Computer networks,
  • Engineering,
  • System theory,
  • Chemical engineering,
  • Renewable energy sources

  • Edition Notes

    Statementby Panagiotis D. Christofides, Jinfeng Liu, David Muñoz de la Peña
    SeriesAdvances in Industrial Control
    ContributionsLiu, Jinfeng, Muñoz de la Peña, David, SpringerLink (Online service)
    The Physical Object
    Format[electronic resource] :
    ID Numbers
    Open LibraryOL25544573M
    ISBN 109780857295811, 9780857295828

      This book describes how control of distributed systems can be advanced by an integration of control, communication, and computation. The global control objectives are met by judicious combinations of local and nonlocal observations taking advantage of various forms of communication exchanges between distributed controllers. Control architectures are . Preface xi About the Authors xv Acknowledgement xvii List of Figures xix List of Tables xxiii 1 Introduction 1 Plant-Wide System 1 Control System Structure of the Plant-Wide System 3 Centralized Control 4 Decentralized Control and Hierarchical Coordinated Decentralized Control 5 Distributed Control 6 Predictive Control 8 What is .

    The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control. Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the. Networked and Distributed Predictive Control: Methods and Nonlinear Process Network Applications A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Chemical Engineering by Jinfeng Liu

    Distributed Model Predictive Control: A Tutorial Review networks) with additional networked (wired or wireless) actuator or sensor devices that have become cheap and easy-to-install. Over the last decade, a series of papers and of distributed model predictive control systems. Our . Event-Based Control and Signal Processing examines the event-based paradigm in control, communication, and signal processing, with a focus on implementation in networked sensor and control systems. Featuring 23 chapters contributed by more than 60 leading researchers from around the world, this book covers.


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Networked and Distributed Predictive Control by Panagiotis D. Christofides Download PDF EPUB FB2

Networked and Distributed Predictive Control presents rigorous, yet practical, methods for the design of networked and distributed predictive control systems. The design of model predictive control systems using Lyapunov-based techniques to account for the influence of asynchronous and delayed measurements is followed by a treatment of networked control architecture Cited by: Networked and Distributed Predictive Control presents rigorous, yet practical, methods for the design of networked and distributed predictive control systems.

The design of model predictive control systems using Lyapunov-based techniques to account for the influence of asynchronous and delayed measurements is followed by a treatment of networked control architecture. Networked and Distributed Predictive Control presents rigorous, yet practical, methods for the design of networked and distributed predictive control systems – the first book to do so.

The design of model predictive control systems using Lyapunov-based Networked and Distributed Predictive Control book accounting for the influence of asynchronous and delayed measurements is Brand: Springer London.

Networked and Distributed Predictive Control | Networked and Distributed Predictive Control presents rigorous, yet practical, methods for the design of networked and distributed predictive control systems - the first book to do so. Get this from a library.

Networked and distributed predictive control: methods and nonlinear process network applications. [Panagiotis D Christofides; Jinfeng Liu; David Muñoz de la Peña;] -- Presents rigorous, yet practical, methods for the design of networked and distributed predictive control systems.

The design of model predictive control systems using Lyapunov-based. springer, Networked and Distributed Predictive Control presents rigorous, yet practical, methods for the design of networked and distributed predictive control systems – the first book to do so.

The design of model predictive control systems using Lyapunov-based techniques accounting for the influence of asynchronous and delayed measurements is followed by a treatment of.

The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control.

Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the Format: Hardcover. This book offers rigorous, yet practical, methods for the design of networked and distributed predictive control systems, including new techniques for system design, insight into likely issues and challenges, and integrated exposition of novel research ked and Distributed Predictive Control presents rigorous, yet practical, methods for the design of networked and Price: $ Get this from a library.

Networked and distributed predictive control: methods and nonlinear process network applications. [Panagiotis D Christofides; Jinfeng Liu; David Muñoz de la Peña] -- Presents rigorous, yet practical, methods for the design of networked and distributed predictive control systems.

The design of model predictive control systems using Lyapunov-based. Abstract. In this chapter, we consider the problem of controlling networked and distributed systems by means of model predictive control (MPC). The basic idea behind MPC is to repeatedly solve an optimal control problem based on a model of the system to be by: 4.

A full understanding of Networked and Distributed Predictive Control requires a basic knowledge of diff erential equations, linear and nonlinear control theory and optimiza- tion methods and the book is intended for academic researchers and graduate students.

Networked and Distributed Predictive Control Autor Panagiotis D. Christofides, Jinfeng Liu, David Mu. This book offers rigorous, yet practical, methods for the design of networked and distributed predictive control systems, including new techniques for system design, insight into likely issues and challenges, and integrated exposi.

Networked and Distributed Predictive Control presents rigorous, yet practical, methods for the design of networked and distributed predictive control systems - the first book to do. This book offers a comprehensive, easy-to-understand overview of receding-horizon control for nonlinear networks.

It presents novel general strategies that can simultaneously handle general nonlinear dynamics, system constraints, and disturbances arising in networked and large-scale systems and which can be widely applied.

Distributed Model Predictive Control for Plant‐Wide Systems. Author(s): Shaoyuan Li; which describe his research accomplishments and interests in predictive control, distributed model predictive control, intelligent adaptive control, and fuzzy intelligent control and its application.

Networked Distributed Predictive Control with. Networked and Distributed Predictive Control presents rigorous, yet practical, methods for the design of networked and distributed predictive control systems - the first book to do so.

The design of model predictive control systems using Lyapunov-based techniques accounting for the influence of asynchronous and delayed measurements is followed Brand: David Munoz De La Pena. A networked control system (NCS) is a system in which the traditional control loops are closed through a communication network such that signals of the system (control and feedback signals) can be exchanged among all components (sensors, controllers, and actuators) through a common network.

Fig. shows a typical structure of an NCS. In comparison with traditional control. Advantage of Predictive Control 9. Distributed Predictive Control 9. Why Distributed Predictive Control 9. What is Distributed Predictive Control Advantage of Distributed Predictive Control Classification of DMPC About this Book Part I FOUNDATION.

2 Model Predictive Control Networked and Distributed Predictive Control presents rigorous, yet practical, methods for the design of networked and distributed predictive control systems – the first book to do so. The design of model predictive control systems using Lyapunov-based techniques accounting for the influence of asynchronous and delayed measurements is.

A Networked Control System (NCS) is a control system wherein the control loops are closed through a communication network. The defining feature of an NCS is that control and feedback signals are exchanged among the system's components in the form of information packages through a network.

Types of communication networks. model predictive control for networked contr ol systems delays [ 1, 2 ], losses [ 3–5 ], and asynchronization [ 6, 7 ], which may degrade performance and e ven cause instability of the.In this paper, a distributed networked control system architecture based on unsupervised and independent Model Predictive Control/Robust Adaptive Fast Fault Estimation (MPC/RAFFE) schemes is proposed.Distributed model predictive control: A tutorial review and future research directions distributed control systems because of its ability to handle input and state constraints and predict the evolution of a system with time while accounting for the effect of Both assumptions are reasonable from process control and networked control Cited by: