Model Identification and Assessment Based on Model Predicted Output
Billings, S.A. and Mao, K.Z.
(1998)
Model Identification and Assessment Based on Model Predicted Output.
Research Report.
ACSE Research Report 714
.
Department of Automatic Control and Systems Engineering
Abstract
Conventional system identification algorithms are based on the minimisation of the one step ahead prediction errors. In this study it is shown that one step ahead predictions do not always provide a good assessment of model quality. The model predicted output which can be considered as the long range prediction is suggested as an alternative criterion for model assessment. Based on this criterion a new system identification algorithm is developed.
Metadata
Item Type:
Monograph
Authors/Creators:
Billings, S.A.
Mao, K.Z.
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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