Sensitivity and a Preferable Alternative to Re-aligned Models for Prediction in MPC
Rossiter, J.A. and Richalet, J.
(2001)
Sensitivity and a Preferable Alternative to Re-aligned Models for Prediction in MPC.
Research Report.
ACSE Research Report 808
.
Department of Automatic Control and Systems Engineering
Abstract
Most papers on predictive control use either state space models with an observer or transfer function models with output realignment for prediction purposes. Here it is shown that this approach can have weaknesses, especially with regard to noise rejection and the independent model approach should soften be preferred.
Metadata
Item Type:
Monograph
Authors/Creators:
Rossiter, J.A.
Richalet, J.
Copyright, Publisher and Additional Information:
The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instances.
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