東華大學圖書館 |

語系: 繁體中文

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

Multivariable predictive control = a...

Lahiri, Sandip Kumar, (1970-)

FindBook

Google Book

Amazon

博客來

Multivariable predictive control = applications in industry /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Multivariable predictive control/ Sandip Kumar Lahiri.
其他題名:	applications in industry /
作者:	Lahiri, Sandip Kumar,
出版者:	Hoboken, NJ :John Wiley & Sons, : 2017.,
面頁冊數:	1 online resource (xxxiii, 267 p.)
標題:	Predictive control. -
電子資源:	https://onlinelibrary.wiley.com/doi/book/10.1002/9781119243434
ISBN:	9781119243434

Multivariable predictive control = applications in industry /
Lahiri, Sandip Kumar,1970-

Multivariable predictive controlapplications in industry /[electronic resource] :Sandip Kumar Lahiri. - 1st ed. - Hoboken, NJ :John Wiley & Sons,2017. - 1 online resource (xxxiii, 267 p.)

Includes bibliographical references and index.

A guide to all practical aspects of building, implementing, managing, and maintaining MPC applications in industrial plants Multivariable Predictive Control: Applications in Industry provides engineers with a thorough understanding of all practical aspects of multivariate predictive control (MPC) applications, as well as expert guidance on how to derive maximum benefit from those systems. Short on theory and long on step-by-step information, it covers everything plant process engineers and control engineers need to know about building, deploying, and managing MPC applications in their companies. MPC has more than proven itself to be one the most important tools for optimising plant operations on an ongoing basis. Companies, worldwide, across a range of industries are successfully using MPC systems to optimise materials and utility consumption, reduce waste, minimise pollution, and maximise production. Unfortunately, due in part to the lack of practical references, plant engineers are often at a loss as to how to manage and maintain MPC systems once the applications have been installed and the consultants and vendors' reps have left the plant. Written by a chemical engineer with two decades of experience in operations and technical services at petrochemical companies, this book fills that regrettable gap in the professional literature. -Provides a cost-benefit analysis of typical MPC projects and reviews commercially available MPC software packages -Details software implementation steps, as well as techniques for successfully evaluating and monitoring software performance once it has been installed -Features case studies and real-world examples from industries, worldwide, illustrating the advantages and common pitfalls of MPC systems -Describes MPC application failures in an array of companies, exposes the root causes of those failures, and offers proven safeguards and corrective measures for avoiding similar failures Multivariable Predictive Control: Applications in Industry is an indispensable resource for plant process engineers and control engineers working in chemical plants, petrochemical companies, and oil refineries in which MPC systems already are operational, or where MPC implementations are being considering.

ISBN: 9781119243434

LCCN: 2017012540Subjects--Topical Terms:

667592
Predictive control.

LC Class. No.: TJ217.6 / .L34 2017

Dewey Class. No.: 629.8

Multivariable predictive control = applications in industry /
LDR:03470cmm a2200313 a 4500 001 2141015
005 20180302170832.0
006 m o d
007 cr |||||||||||
008 181211s2017 njua ob 001 0 eng
010 $a 2017012540
020 $a 9781119243434 $q (electronic bk.)
020 $a 1119243432 $q (electronic bk.)
020 $a 9781119243519 $q (pdf)
020 $a 1119243513 $q (pdf)
020 $a 9781119243595 $q (epub)
020 $a 1119243599 $q (epub)
020 $z 9781119243601 $q (cloth)
035 $a 002599245
040 $a DLC $b eng $c DLC $d OCLCO $d OCLCQ $d OCLCF $d OCLCQ $d N $d YDX $d IDEBK $d DG1 $d YDX $d UIU $d EBLCP $d RECBK $d NRC $d DEBSZ $d TEFOD $d CNCGM $d UPM $d MERER $d OCLCQ
050 1 4 $a TJ217.6 $b .L34 2017
082 0 0 $a 629.8 $2 23
100 1 $a Lahiri, Sandip Kumar, $d 1970- $3 3318769
245 1 0 $a Multivariable predictive control $h [electronic resource] : $b applications in industry / $c Sandip Kumar Lahiri.
250 $a 1st ed.
260 $a Hoboken, NJ : $b John Wiley & Sons, $c 2017.
300 $a 1 online resource (xxxiii, 267 p.)
504 $a Includes bibliographical references and index.
520 $a A guide to all practical aspects of building, implementing, managing, and maintaining MPC applications in industrial plants Multivariable Predictive Control: Applications in Industry provides engineers with a thorough understanding of all practical aspects of multivariate predictive control (MPC) applications, as well as expert guidance on how to derive maximum benefit from those systems. Short on theory and long on step-by-step information, it covers everything plant process engineers and control engineers need to know about building, deploying, and managing MPC applications in their companies. MPC has more than proven itself to be one the most important tools for optimising plant operations on an ongoing basis. Companies, worldwide, across a range of industries are successfully using MPC systems to optimise materials and utility consumption, reduce waste, minimise pollution, and maximise production. Unfortunately, due in part to the lack of practical references, plant engineers are often at a loss as to how to manage and maintain MPC systems once the applications have been installed and the consultants and vendors' reps have left the plant. Written by a chemical engineer with two decades of experience in operations and technical services at petrochemical companies, this book fills that regrettable gap in the professional literature. -Provides a cost-benefit analysis of typical MPC projects and reviews commercially available MPC software packages -Details software implementation steps, as well as techniques for successfully evaluating and monitoring software performance once it has been installed -Features case studies and real-world examples from industries, worldwide, illustrating the advantages and common pitfalls of MPC systems -Describes MPC application failures in an array of companies, exposes the root causes of those failures, and offers proven safeguards and corrective measures for avoiding similar failures Multivariable Predictive Control: Applications in Industry is an indispensable resource for plant process engineers and control engineers working in chemical plants, petrochemical companies, and oil refineries in which MPC systems already are operational, or where MPC implementations are being considering.
588 $a Description based on online resource; title from digital title page (viewed on August 30, 2017)
650 0 $a Predictive control. $3 667592
650 0 $a Multivariate analysis. $3 517467
856 4 0 $u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119243434