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: Advanced Control of Industrial Processes
    sub title: Structures and Algorithms
  name:
    name part: Tatjewski, Piotr.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxk
    date issued: 2007
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIX, 332 p. online resource.
  abstract: Advanced Control of Industrial Processes presents the concepts and algorithms of advanced industrial process control and on-line optimisation within the framework of a multilayer structure. Relatively simple unconstrained nonlinear fuzzy control algorithms and linear predictive control laws are covered, as are more involved constrained and nonlinear model predictive control (MPC) algorithms and on-line set-point optimisation techniques. The major topics and key features are: • Development and discussion of a multilayer control structure with interrelated direct control, set-point control and optimisation layers, as a framework for the subject of the book. • Systematic presentation and stability analysis of fuzzy feedback control algorithms in Takagi-Sugeno structures for state-space and input-output models, in discrete and continuous time, presented as natural generalisations of well-known practical linear control laws (like the PID law) to the nonlinear case. • Thorough derivation of most practical MPC algorithms with linear process models (dynamic matrix control, generalised predictive control, and with state-space models), both as fast explicit control laws (also embedded into appropriate structures to cope with process input constraints), and as more involved numerical constrained MPC algorithms. • Development of computationally effective MPC structures for nonlinear process models, utilising on-line model linearisations and fuzzy reasoning. • General presentation of the subject of on-line set-point improvement and optimisation, together with iterative algorithms capable of coping with uncertainty in process models and disturbance estimates. • Complete theoretical stability analysis of fuzzy Takagi-Sugeno control systems, discussion of stability and feasibility issues of MPC algorithms as well as of tuning aspects, discussion of applicability and convergence of on-line set-point improvement algorithms. • Thorough illustration of the methodologies and algorithms …
  table of contents: Multilayer Control Structure -- Model-based Fuzzy Control -- Model-based Predictive Control -- Set-point Optimization.
  note: by Piotr Tatjewski.
  subject:
    topic: Engineering
  subject:
    topic: Chemical engineering
  subject:
    topic: Calculus of variations
  subject:
    topic: Control engineering
  subject:
    topic: Industrial engineering
  subject:
    topic: Production engineering
  subject:
    topic: Engineering
  subject:
    topic: Control
  subject:
    topic: Industrial Chemistry/Chemical Engineering
  subject:
    topic: Calculus of Variations and Optimal Control; Optimization
  subject:
    topic: Industrial and Production Engineering
  classification: TJ212-225
  classification: 629.8
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Advances in Industrial Control
  identifier: 9781846286353
  identifier: http://dx.doi.org/10.1007/978-1-84628-635-3
  record info:
    record creation date: 100301
    record change date: 20151204161844.0
    record identifier: 978-1-84628-635-3