cam a22 4 4500 390164445 CHVBK 20201009005412.0 cr ||||||||||| 161201s2016 gw s 00 eng autom. Import ab Springer MARC Records 08.03.2017/BUME 978-3-319-42258-9 E-Book 978-3-319-42257-2 Druckausgabe 10.1007/978-3-319-42258-9 doi (LIBIB)000403418 (IDSSG)000895969 Springer ger LI-VaLIL FLFHL rda HD30.23 658.40301 23 DEAGICB3AB4C1A72DE77EC12580540046968E iCapture Skormin Victor A. Verfasser aut Introduction to process control analysis, mathematical modeling, control and optimization by Victor A. Skormin Cham Springer International Publishing 2016 Online-Ressource text file PDF rda Springer texts in business and economics (LIBIB)000343105 323771890 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 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.- Business Operations research Decision making Management information systems Industrial management Industrial engineering Production engineering Printed edition 9783319422572 http://dx.doi.org/10.1007/978-3-319-42258-9 Download für Uni Volltext BK020053 XK020053 XK020000 fhlseb libib X noalma ids I bw FL IDSSG HSG HSG ONL HONL000895969 LIBIB FLFHL FLFHL OL - NELFHL1702 Zugriff nur vom Uni-Campus LIBIB 100 1- Skormin Victor A. Verfasser aut LIBIB 490 0- Springer texts in business and economics (LIBIB)000343105 323771890 LIBIB 856 -- http://dx.doi.org/10.1007/978-3-319-42258-9 Download für Uni Volltext IDSSG 100 1- Skormin Victor A. Verfasser aut IDSSG 490 1- Springer Texts in Business and Economics 2192-4333 IDSSG 776 08 Printed edition 9783319422572 IDSSG 856 40 https://doi.org/10.1007/978-3-319-42258-9 Full text for the University of St. Gallen SWISSBIB 390164445