An iterative least squares estimation algorithm for controlled moving average systems based on matrix decomposition

An iterative least squares parameter estimation algorithm is developed for controlled moving average systems based on matrix decomposition. The proposed algorithm avoids repeatedly computing the inverse of the data product moment matrix with large sizes at each iteration and has a high computational efficiency. A numerical example indicates that the proposed algorithm is effective.