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Nonlinear Model Based Process Control

Nonlinear Model Based Process Controlaf R D Berber
Bag om Nonlinear Model Based Process Control

The increasingly competitive environment within which modern industry has to work means that processes have to be operated over a wider range of conditions in order to meet constantly changing performance targets. Add to this the fact that many industrial operations are nonlinear, and the need for on-line control algorithms for nonlinear processes becomes clear. Major progress has been booked in constrained model-based control and important issues of nonlinear process control have been solved. This text surveys the state-of-the-art in nonlinear model-based control technology, by writers who have actually created the scientific profile. A broad range of issues are covered in depth, from traditional nonlinear approaches to nonlinear model predictive control, from nonlinear process identification and state estimation to control-integrated design. Advances in the control of inverse response and unstable processes are presented. Comparisons with linear control are given, and case studies are used for illustration.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9780792352204
  • Indbinding:
  • Hardback
  • Sideantal:
  • 896
  • Udgivet:
  • 31. august 1998
  • Størrelse:
  • 166x244x50 mm.
  • Vægt:
  • 1347 g.
  • Ukendt - mangler pt..
Forlænget returret til d. 31. januar 2025
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Beskrivelse af Nonlinear Model Based Process Control

The increasingly competitive environment within which modern industry has to work means that processes have to be operated over a wider range of conditions in order to meet constantly changing performance targets. Add to this the fact that many industrial operations are nonlinear, and the need for on-line control algorithms for nonlinear processes becomes clear. Major progress has been booked in constrained model-based control and important issues of nonlinear process control have been solved. This text surveys the state-of-the-art in nonlinear model-based control technology, by writers who have actually created the scientific profile. A broad range of issues are covered in depth, from traditional nonlinear approaches to nonlinear model predictive control, from nonlinear process identification and state estimation to control-integrated design. Advances in the control of inverse response and unstable processes are presented. Comparisons with linear control are given, and case studies are used for illustration.

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