rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Introduction to Process Control
    sub title: Analysis, Mathematical Modeling, Control and Optimization
  name:
    name part: Skormin, Victor A.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2016
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVII, 254 p. 106 illus., 50 illus. in color. online resource.
  abstract: 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 manufacturi…
  table of contents: Statistical Methods and their Applications -- Mathematical Description of Manufacturing Processes -- Computer Control of Manufacturing Processes -- Methods and Models of Optimazation. .
  note: by Victor A. Skormin.
  subject:
    topic: Business
  subject:
    topic: Operations research
  subject:
    topic: Decision making
  subject:
    topic: Management information systems
  subject:
    topic: Industrial management
  subject:
    topic: Industrial engineering
  subject:
    topic: Production engineering
  subject:
    topic: Business and Management
  subject:
    topic: Operation Research/Decision Theory
  subject:
    topic: Business Process Management
  subject:
    topic: Industrial and Production Engineering
  classification: HD30.23
  classification: 658.40301
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Texts in Business and Economics
  identifier: 9783319422589
  identifier: http://dx.doi.org/10.1007/978-3-319-42258-9
  record info:
    record creation date: 161019
    record change date: 20161019155604.0
    record identifier: 978-3-319-42258-9