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A quadratic constraint approach to m...

Ha, Quang.

A quadratic constraint approach to model predictive control of interconnected systems

Record Type:	Electronic resources : Monograph/item
Title/Author:	A quadratic constraint approach to model predictive control of interconnected systemsby Anthony Tri Tran C., Quang Ha.
Author:	Tri Tran C., Anthony.
other author:	Ha, Quang.
Published:	Singapore :Springer Singapore :2018.
Description:	xvii, 236 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Predictive control.
Online resource:	http://dx.doi.org/10.1007/978-981-10-8409-6
ISBN:	9789811084096$q(electronic bk.)

A quadratic constraint approach to model predictive control of interconnected systems
Tri Tran C., Anthony.

A quadratic constraint approach to model predictive control of interconnected systems[electronic resource] /by Anthony Tri Tran C., Quang Ha. - Singapore :Springer Singapore :2018. - xvii, 236 p. :ill., digital ;24 cm. - Studies in systems, decision and control,v.1482198-4182 ;. - Studies in systems, decision and control ;v.3..

Introduction -- Quadratic Constraint for Decentralised Model Predictive Control -- Quadratic Constraint for Parallel Splitting Systems -- Quadratic Constraint for Semi-Automatic Control -- Quadratic Constraint with Data Losses.

This book focuses on the stabilization and model predictive control of interconnected systems with mixed connection configurations. It introduces the concept of dissipation-based quadratic constraint for developing attractivity assurance methods for interconnected systems. In order to develop these methods, distributed and decentralized architectures are employed, whereby the communication between subsystems is fully connected, partially connected, or completely disconnected. Given that the control inputs are entirely or partially decoupled between subsystems and no additional constraints are imposed on the interactive variables beyond the coupling constraint itself, the proposed approaches can be used with various types of systems and applications. Further, the book describes how the effects of coupling delays and data losses in device networks are resolved. From a practical perspective, the innovations presented are of benefit in applications in a broad range of fields, including the process and manufacturing industries, networked robotics, and network-centric systems such as chemical process systems, power systems, telecommunication networks, transportation networks, and, no less importantly, supply chain automation.

ISBN: 9789811084096$q(electronic bk.)

Standard No.: 10.1007/978-981-10-8409-6doiSubjects--Topical Terms:

182316
Predictive control.

LC Class. No.: TJ217.6

Dewey Class. No.: 003.5

A quadratic constraint approach to model predictive control of interconnected systems
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245 1 2 $a A quadratic constraint approach to model predictive control of interconnected systems $h [electronic resource] / $c by Anthony Tri Tran C., Quang Ha.
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490 1 $a Studies in systems, decision and control, $x 2198-4182 ; $v v.148
505 0 $a Introduction -- Quadratic Constraint for Decentralised Model Predictive Control -- Quadratic Constraint for Parallel Splitting Systems -- Quadratic Constraint for Semi-Automatic Control -- Quadratic Constraint with Data Losses.
520 $a This book focuses on the stabilization and model predictive control of interconnected systems with mixed connection configurations. It introduces the concept of dissipation-based quadratic constraint for developing attractivity assurance methods for interconnected systems. In order to develop these methods, distributed and decentralized architectures are employed, whereby the communication between subsystems is fully connected, partially connected, or completely disconnected. Given that the control inputs are entirely or partially decoupled between subsystems and no additional constraints are imposed on the interactive variables beyond the coupling constraint itself, the proposed approaches can be used with various types of systems and applications. Further, the book describes how the effects of coupling delays and data losses in device networks are resolved. From a practical perspective, the innovations presented are of benefit in applications in a broad range of fields, including the process and manufacturing industries, networked robotics, and network-centric systems such as chemical process systems, power systems, telecommunication networks, transportation networks, and, no less importantly, supply chain automation.
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