2000 Volume 36 Issue 7 Pages 575-582
For the control design, it is important to build a good model. To identify the model parameter exactly, it is necessary to use data which are less affected by the disturbance or modelling uncertainty. We propose that it is important to evaluate the upper bound of the parameter estimation error when the disturbance and the unstructured model uncertainty exist. It can be used to decide the optimal identification input and frequency weight for least square criterion.