On the improvement of the adaptation behaviour of recursive parameter estimation algorithms through nonlinear, dynamic pre-control

A method is introduced for improving the tracking or identification behaviour of recursive parameter estimation algorithms. The method utilizes available, measured information from the process or information which acts on the process. The information is processed by a nonlinear, dynamic precontrol algorithm. Measurement updates are transformed into approximate parameter updates that are used as reference values in the classical estimation algorithm. Aircraft control has been chosen as an application example, and 6-degree-of-freedom simulation results are excellent