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
