Moving identification via weighted least-squares estimation

Abstract

Abstract Moving identification using weighted least-squares estimation is developed. Two weighting factors are used: one for discarding old data, the other for adding new data, and these two weighting factors are chosen to ensure that the estimated parameters are convergent. The sufficient conditions for the convergent property are also presented. The proposed method is suitable for time-varying systems.