On-line system identification with an adjustable estimation interval

Abstract

Abstract On-line system identification with an adjustable estimation interval based on a continuous-time model is developed. The algorithm of interval selection depends on measurement noise, adaptive gain, and modelling error. Parameter estimation is carried out using recursive formulae via a weighted least-squares estimation. Illustrative examples are presented to show the potential of this method.