A Study on Reduced Variance Self-Tuning Algorithm Using a Variable Forgetting Factor

시변 망각 인자를 사용하는 최소 자승 추정의 극점 -배치 자기동조 알고리즘에 관한 연구

Pole assignment controller with variable forgetting factor is generalizaed to allow the output and/or input variance to be reduced. The algorithm can give significant reductions in variance for little extra computational effort and is presented for servo-tracking using leat-squares estimation. Moreover, the use of a variable forgetting factor with correct choice of information bound can avoid 'blowing-up' of the covariance matrix of the estimates and subsequent unstable control.