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Autor(en): 
  • Victor A. Skormin
  • Introduction to Process Control: Analysis, Mathematical Modeling, Control and Optimization 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 4 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Juni 2018  
    Genre:  Wirtschaft / Recht 
     
    B / Business and Management / Business mathematics & systems / Business Process Management / Decision Making / Industrial and Production Engineering / Industrial Engineering / Industrial Management / IT in Business / Management decision making / Management information systems / Management science / Operations Research / Operations Research and Decision Theory / Operations Research/Decision Theory / Production engineering
    ISBN:  9783319825403 
    EAN-Code: 
    9783319825403 
    Verlag:  Springer Nature EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  Springer Texts in Business and Economics  
    Dimensionen:  H 235 mm / B 155 mm / D 14 mm 
    Gewicht:  4161 gr 
    Seiten:  254 
    Illustration:  XVII, 254 p. 106 illus., 50 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Zus. Info:  Previously published in hardcover 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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:

    1.  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.
    2. 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.
    3. 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.
    4. 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.

      
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