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Advanced Control of Industrial Processes

Bag om Advanced Control of Industrial Processes

"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. Major topics and key features include: Derivation of practical MPC algorithms with linear process models; 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; Complete theoretical stability analysis of fuzzy Takagi-Sugeno control systems; Illustration of the methodologies and algorithms by worked examples in the text and by results of simulations based on industrial process models.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9781849966320
  • Indbinding:
  • Paperback
  • Sideantal:
  • 356
  • Udgivet:
  • 21. oktober 2010
  • Størrelse:
  • 155x20x235 mm.
  • Vægt:
  • 540 g.
  • 8-11 hverdage.
  • 16. januar 2025
På lager
Forlænget returret til d. 31. januar 2025
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Beskrivelse af Advanced Control of Industrial Processes

"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.

Major topics and key features include: Derivation of practical MPC algorithms with linear process models; 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; Complete theoretical stability analysis of fuzzy Takagi-Sugeno control systems; Illustration of the methodologies and algorithms by worked examples in the text and by results of simulations based on industrial process models.

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