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Introduction to Process Control Analysis, Mathematical Modeling, Control and Optimization /
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 multi...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2016.
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| Edición: | 1st ed. 2016. |
| Colección: | Springer Texts in Business and Economics,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
| LEADER | 00000nam a22000005i 4500 | ||
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| 001 | 978-3-319-42258-9 | ||
| 003 | DE-He213 | ||
| 005 | 20220116232120.0 | ||
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| 008 | 161019s2016 sz | s |||| 0|eng d | ||
| 020 | |a 9783319422589 |9 978-3-319-42258-9 | ||
| 024 | 7 | |a 10.1007/978-3-319-42258-9 |2 doi | |
| 050 | 4 | |a T57.6-.97 | |
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| 100 | 1 | |a Skormin, Victor A. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Introduction to Process Control |h [electronic resource] : |b Analysis, Mathematical Modeling, Control and Optimization / |c by Victor A. Skormin. |
| 250 | |a 1st ed. 2016. | ||
| 264 | 1 | |a Cham : |b Springer International Publishing : |b Imprint: Springer, |c 2016. | |
| 300 | |a XVII, 254 p. 106 illus., 50 illus. in color. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Springer Texts in Business and Economics, |x 2192-4341 | |
| 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 Operations research. | |
| 650 | 0 | |a Information technology-Management. | |
| 650 | 0 | |a Industrial engineering. | |
| 650 | 0 | |a Production engineering. | |
| 650 | 1 | 4 | |a Operations Research and Decision Theory. |
| 650 | 2 | 4 | |a Business Process Management. |
| 650 | 2 | 4 | |a Industrial and Production Engineering. |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783319422572 |
| 776 | 0 | 8 | |i Printed edition: |z 9783319422596 |
| 776 | 0 | 8 | |i Printed edition: |z 9783319825403 |
| 830 | 0 | |a Springer Texts in Business and Economics, |x 2192-4341 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-3-319-42258-9 |z Texto Completo |
| 912 | |a ZDB-2-BUM | ||
| 912 | |a ZDB-2-SXBM | ||
| 950 | |a Business and Management (SpringerNature-41169) | ||
| 950 | |a Business and Management (R0) (SpringerNature-43719) | ||