東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Introduction to process control = an...

Skormin, Victor A.

Linked to FindBook

Google Book

Amazon

博客來

Introduction to process control = analysis, mathematical modeling, control and optimization /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Introduction to process control/ by Victor A. Skormin.
Reminder of title:	analysis, mathematical modeling, control and optimization /
Author:	Skormin, Victor A.
Published:	Cham :Springer International Publishing : : 2016.,
Description:	xvii, 254 p. :ill., digital ;24 cm.
[NT 15003449]:	Statistical Methods and their Applications -- Mathematical Description of Manufacturing Processes -- Computer Control of Manufacturing Processes -- Methods and Models of Optimazation.
Contained By:	Springer eBooks
Subject:	Business. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-42258-9
ISBN:	9783319422589

Introduction to process control = analysis, mathematical modeling, control and optimization /
Skormin, Victor A.

Introduction to process controlanalysis, mathematical modeling, control and optimization /[electronic resource] :by Victor A. Skormin. - Cham :Springer International Publishing :2016. - xvii, 254 p. :ill., digital ;24 cm. - Springer texts in business and economics,2192-4333. - Springer texts in business and economics..

Statistical Methods and their Applications -- Mathematical Description of Manufacturing Processes -- Computer Control of Manufacturing Processes -- Methods and Models of Optimazation.

This textbook is intended for an introductory graduate level on process control, taught in most engineering curricula. It focuses on the statistical techniques and methods of control and system optimization needed for the mathematical modeling, analysis, simulation, control and optimization of multivariable manufacturing processes. In four sections, it covers: Relevant mathematical methods, including random events, variables and processes, and their characteristics; estimation and confidence intervals; Bayes applications; correlation and regression analysis; statistical cluster analysis; and singular value decomposition for classification applications. Mathematical description of manufacturing processes, including static and dynamic models; model validation; confidence intervals for model parameters; principal component analysis; conventional and recursive least squares procedures; nonlinear least squares; and continuous-time, discrete-time, s-domain and Z-domain models. Control of manufacturing processes, including transfer function/transfer matrix models; state-variable models; methods of discrete-time classical control; state variable discrete-time control; state observers/estimators in control systems; methods of decoupling control; and methods of adaptive control. Methods and applications of system optimization, including unconstrained and constrained optimization; analytical and numerical optimization procedures; use of penalty functions; methods of linear programming; gradient methods; direct search methods; genetic optimization; methods and applications of dynamic programming; and applications to estimation, design, control, and planning. Each section of the book will include end-of-chapter exercises, and the book will be suitable for any systems, electrical, chemical, or industrial engineering program, as it focuses on the processes themselves, and not on the product being manufactured. Students will be able to obtain a mathematical model of any manufacturing process, to design a computer-based control system for a particular continuous manufacturing process, and be able to formulate an engineering problem in terms of optimization, as well as the ability to choose and apply the appropriate optimization technique.

ISBN: 9783319422589

Standard No.: 10.1007/978-3-319-42258-9doiSubjects--Topical Terms:

627273
Business.

LC Class. No.: HD30.23

Dewey Class. No.: 658.40301

Introduction to process control = analysis, mathematical modeling, control and optimization /
LDR:03519nmm a2200337 a 4500 001 2053527
003 DE-He213
005 20161019155604.0
006 m d
007 cr nn 008maaau
008 170510s2016 gw s 0 eng d
020 $a 9783319422589 $q (electronic bk.)
020 $a 9783319422572 $q (paper)
024 7 $a 10.1007/978-3-319-42258-9 $2 doi
035 $a 978-3-319-42258-9
040 $a GP $c GP
041 0 $a eng
050 4 $a HD30.23
072 7 $a KJT $2 bicssc
072 7 $a KJMD $2 bicssc
072 7 $a BUS049000 $2 bisacsh
082 0 4 $a 658.40301 $2 23
090 $a HD30.23 $b .S628 2016
100 1 $a Skormin, Victor A. $3 892934
245 1 0 $a Introduction to process control $h [electronic resource] : $b analysis, mathematical modeling, control and optimization / $c by Victor A. Skormin.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xvii, 254 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer texts in business and economics, $x 2192-4333
505 0 $a Statistical Methods and their Applications -- Mathematical Description of Manufacturing Processes -- Computer Control of Manufacturing Processes -- Methods and Models of Optimazation.
520 $a This textbook is intended for an introductory graduate level on process control, taught in most engineering curricula. It focuses on the statistical techniques and methods of control and system optimization needed for the mathematical modeling, analysis, simulation, control and optimization of multivariable manufacturing processes. In four sections, it covers: Relevant mathematical methods, including random events, variables and processes, and their characteristics; estimation and confidence intervals; Bayes applications; correlation and regression analysis; statistical cluster analysis; and singular value decomposition for classification applications. Mathematical description of manufacturing processes, including static and dynamic models; model validation; confidence intervals for model parameters; principal component analysis; conventional and recursive least squares procedures; nonlinear least squares; and continuous-time, discrete-time, s-domain and Z-domain models. Control of manufacturing processes, including transfer function/transfer matrix models; state-variable models; methods of discrete-time classical control; state variable discrete-time control; state observers/estimators in control systems; methods of decoupling control; and methods of adaptive control. Methods and applications of system optimization, including unconstrained and constrained optimization; analytical and numerical optimization procedures; use of penalty functions; methods of linear programming; gradient methods; direct search methods; genetic optimization; methods and applications of dynamic programming; and applications to estimation, design, control, and planning. Each section of the book will include end-of-chapter exercises, and the book will be suitable for any systems, electrical, chemical, or industrial engineering program, as it focuses on the processes themselves, and not on the product being manufactured. Students will be able to obtain a mathematical model of any manufacturing process, to design a computer-based control system for a particular continuous manufacturing process, and be able to formulate an engineering problem in terms of optimization, as well as the ability to choose and apply the appropriate optimization technique.
650 0 $a Business. $3 627273
650 0 $a Operations research. $3 547123
650 0 $a Decision making. $3 517204
650 0 $a Management information systems. $3 528143
650 0 $a Industrial management. $3 529072
650 0 $a Industrial engineering. $3 526216
650 0 $a Production engineering. $3 654420
650 1 4 $a Business and Management. $2 eflch $3 1485455
650 2 4 $a Operation Research/Decision Theory. $3 1620900
650 2 4 $a Business Process Management. $3 2134548
650 2 4 $a Industrial and Production Engineering. $3 891024
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Springer texts in business and economics. $3 1565849
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-42258-9
950 $a Business and Management (Springer-41169)