Minimax long range parameter estimation

This paper derives a robust long range prediction error estimator. The long range minimax prediction error (MPE) algorithm is developed by combining the robust (H_∞) linear predictor and long range prediction error method. The resulting identification algorithm, which minimizes the peaks of the error spectrum rather than its integral on the unit circle, is shown to have better robustness properties than recursive least squares with ad hoc data prefiltering. The frequency domain properties of the MPE estimator indicate that the MPE estimator is equivalent to the RLS algorithm with prefilter. The MPE estimator can provide a better estimated model for the model based long range predictive controller. The resulting self-tuning predictive controller will have better overall stability and robustness properties then the H ₂ self-tuning algorithms