Nonlinear Model Based Process Control: Proceedings of the NATO Advanced Study Institute, Antalya, Turkey, August 10-20, 1997: v. 353 (NATO Science Series E:) - Hardcover

9780792352204: Nonlinear Model Based Process Control: Proceedings of the NATO Advanced Study Institute, Antalya, Turkey, August 10-20, 1997: v. 353 (NATO Science Series E:)

Hardcover

ISBN 10: 0792352203 ISBN 13: 9780792352204

Verlag: Kluwer Academic Publishers, 1998

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.

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Rese�a del editor

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.

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