Nonlinear Model Based Process Control

Nonlinear Model Based Process Control

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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. The present book 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. Recent 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.Design and control of batch reactors - an industrial viewpoint. Comput. Chem. Eng., 19(Suppl.):S357-S368. 1995. 25. P.E. Gill. W. Murray, M.A. Saunders, and M.H. Wright. Usera#39;s Guide for NPSOL, Version 4.0. Systems Optimization Laboratoryanbsp;...


Title:Nonlinear Model Based Process Control
Author: Rıdvan Berber, Costas Kravaris, North Atlantic Treaty Organization. Scientific Affairs Division
Publisher:Springer Science & Business Media - 1998-01-01
ISBN-13:

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