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Uncertainty-aware integration of con...

Charitopoulos, Vassilis M.

Uncertainty-aware integration of control with process operations and multi-parametric programming under global uncertainty

Record Type:	Electronic resources : Monograph/item
Title/Author:	Uncertainty-aware integration of control with process operations and multi-parametric programming under global uncertaintyby Vassilis M. Charitopoulos.
Author:	Charitopoulos, Vassilis M.
Published:	Cham :Springer International Publishing :2020.
Description:	xxxiii, 266 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Uncertainty (Information theory)
Online resource:	https://doi.org/10.1007/978-3-030-38137-0
ISBN:	9783030381370$q(electronic bk.)

Uncertainty-aware integration of control with process operations and multi-parametric programming under global uncertainty
Charitopoulos, Vassilis M.

Uncertainty-aware integration of control with process operations and multi-parametric programming under global uncertainty[electronic resource] /by Vassilis M. Charitopoulos. - Cham :Springer International Publishing :2020. - xxxiii, 266 p. :ill., digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

Thesis Background -- Parametric Optimisation: 65 Years of Developments and Status Quo -- Multi-parametric Linear and Mixed Integer Linear Programming Under Global Uncertainty -- Towards Exact Multi-setpoint Explicit Controllers for Enterprise Wide Optimisation -- Open-loop Integration of Planning, Scheduling and Optimal Control: Overview, Challenges and Model Formulations -- Closed-loop Integration of Planning, Scheduling and Multi-parametric Nonlinear Control -- A Hybrid Framework for the Uncertainty-aware Integration of Planning, Scheduling and Explicit Control -- Conclusions and Future Work.

This book introduces models and methodologies that can be employed towards making the Industry 4.0 vision a reality within the process industries, and at the same time investigates the impact of uncertainties in such highly integrated settings. Advances in computing power along with the widespread availability of data have led process industries to consider a new paradigm for automated and more efficient operations. The book presents a theoretically proven optimal solution to multi-parametric linear and mixed-integer linear programs and efficient solutions to problems such as process scheduling and design under global uncertainty. It also proposes a systematic framework for the uncertainty-aware integration of planning, scheduling and control, based on the judicious coupling of reactive and proactive methods. Using these developments, the book demonstrates how the integration of different decision-making layers and their simultaneous optimisation can enhance industrial process operations and their economic resilience in the face of uncertainty.

ISBN: 9783030381370$q(electronic bk.)

Standard No.: 10.1007/978-3-030-38137-0doiSubjects--Topical Terms:

206405
Uncertainty (Information theory)

LC Class. No.: Q375 / .C437 2020

Dewey Class. No.: 003.54

Uncertainty-aware integration of control with process operations and multi-parametric programming under global uncertainty
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520 $a This book introduces models and methodologies that can be employed towards making the Industry 4.0 vision a reality within the process industries, and at the same time investigates the impact of uncertainties in such highly integrated settings. Advances in computing power along with the widespread availability of data have led process industries to consider a new paradigm for automated and more efficient operations. The book presents a theoretically proven optimal solution to multi-parametric linear and mixed-integer linear programs and efficient solutions to problems such as process scheduling and design under global uncertainty. It also proposes a systematic framework for the uncertainty-aware integration of planning, scheduling and control, based on the judicious coupling of reactive and proactive methods. Using these developments, the book demonstrates how the integration of different decision-making layers and their simultaneous optimisation can enhance industrial process operations and their economic resilience in the face of uncertainty.
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