Uncertainty-aware Integration Of Control With Process Operations And Multi-parametric Programming Under Global Uncertainty (springer Theses) 🔍
Vassilis M Charitopoulos; SpringerLink (Online service) Springer International Publishing, Imprint Springer, Springer Nature, Cham, 2020
英语 [en] · 中文 [zh] · FB2 · 3.3MB · 2020 · 📕 小说类图书 · 🚀/lgli/zlib · Save
描述
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.
Erscheinungsdatum: 05.02.2020
备用文件名
zlib/no-category/Vassilis M. Charitopoulos/Uncertainty-aware Integration of Control with Process Operations and Multi-parametric Programming Under Global Uncertainty_15031633.fb2
备选作者
Charitopoulos, Vassilis M.
备选作者
VASILEIOS CHARITOPOULOS
备用出版商
Springer Nature Switzerland AG
备用版本
Springer Theses, Recognizing Outstanding Ph.D. Research, 1st edition 2020, Cham, 2020
备用版本
Place of publication not identified, 2020
备用版本
Switzerland, Switzerland
备用版本
1, 2020-03-31
备用版本
Feb 05, 2020
备用版本
1, 20200205
元数据中的注释
Source title: Uncertainty-aware Integration of Control with Process Operations and Multi-parametric Programming Under Global Uncertainty (Springer Theses)
开源日期
2021-05-28
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