UNBIASED ESTIMATION IN DYNAMIC DATA RECONCILIATION

A computationally fast technique accurately estimates process variable s when conditions are dynamic due to changes in steady states. The pro cess variable estimators are unbiased and have known distributions. Th us, confidence intervals for true values of process variables are prov ided. The formulation of this technique was motivated by a recursive, dynamic data reconciliation technique that obtains very accurate estim ators. These two techniques are compared in terms of computational spe ed and accuracy of estimators. The proposed technique is computational ly faster, but not as accurate when variances of process measurements are large. However, the accuracy of the proposed estimators is shown t o approach that of the recursive technique by iteratively recalculatin g estimates and when measurement variances decrease.