語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Uncertainty-aware integration of con...
~
Charitopoulos, Vassilis M.
FindBook
Google Book
Amazon
博客來
Uncertainty-aware integration of control with process operations and multi-parametric programming under global uncertainty
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Uncertainty-aware integration of control with process operations and multi-parametric programming under global uncertainty/ by Vassilis M. Charitopoulos.
作者:
Charitopoulos, Vassilis M.
出版者:
Cham :Springer International Publishing : : 2020.,
面頁冊數:
xxxiii, 266 p. :ill., digital ;24 cm.
內容註:
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.
Contained By:
Springer eBooks
標題:
Uncertainty (Information theory) -
電子資源:
https://doi.org/10.1007/978-3-030-38137-0
ISBN:
9783030381370
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
Standard No.: 10.1007/978-3-030-38137-0doiSubjects--Topical Terms:
587701
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
LDR
:02758nmm a2200337 a 4500
001
2216050
003
DE-He213
005
20200708134646.0
006
m d
007
cr nn 008maaau
008
201120s2020 sz s 0 eng d
020
$a
9783030381370
$q
(electronic bk.)
020
$a
9783030381363
$q
(paper)
024
7
$a
10.1007/978-3-030-38137-0
$2
doi
035
$a
978-3-030-38137-0
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
Q375
$b
.C437 2020
072
7
$a
TDC
$2
bicssc
072
7
$a
SCI013060
$2
bisacsh
072
7
$a
TDC
$2
thema
082
0 4
$a
003.54
$2
23
090
$a
Q375
$b
.C473 2020
100
1
$a
Charitopoulos, Vassilis M.
$3
3448060
245
1 0
$a
Uncertainty-aware integration of control with process operations and multi-parametric programming under global uncertainty
$h
[electronic resource] /
$c
by Vassilis M. Charitopoulos.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2020.
300
$a
xxxiii, 266 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Springer theses,
$x
2190-5053
505
0
$a
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.
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.
650
0
$a
Uncertainty (Information theory)
$3
587701
650
0
$a
System theory.
$3
525574
650
1 4
$a
Industrial Chemistry/Chemical Engineering.
$3
890826
650
2 4
$a
Computational Mathematics and Numerical Analysis.
$3
891040
650
2 4
$a
Industrial and Production Engineering.
$3
891024
650
2 4
$a
Operating Systems.
$3
892491
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
830
0
$a
Springer theses.
$3
1314442
856
4 0
$u
https://doi.org/10.1007/978-3-030-38137-0
950
$a
Chemistry and Materials Science (Springer-11644)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9390954
電子資源
11.線上閱覽_V
電子書
EB Q375 .C437 2020
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入