A PROCEDURE FOR SELECTING BEST IDENTIFIABLE PARAMETERS IN CALIBRATINGACTIVATED-SLUDGE MODEL NO.1 TO FULL-SCALE PLANT-DATA

A systematic procedure for selecting identifiable parameter subsets fo r a given set of measured outputs is proposed. The aim is to only sele ct those parameters which can be estimated uniquely from the dataset u sed. The proposed procedure consists of first selecting a reduced set of most sensitive parameters by sensitivity analysis and subsequently selecting identifiable parameter subsets using the Fisher information matrix. For a particular set of outputs obtained from a typical calibr ation exercise at a carrousel-type nitrogen removal plant, parameter s ubsets ranging from two to eight parameters were selected by this proc edure. The procedure proved successful as the parameter subsets thus s elected could be estimated accurately from simulated data without and with noise as well as from real data. However, the procedure is based on a property which is local in parameter space. Consequently, as an a priori assumption on the parameter vales has to be made at the start of the procedure, the selection results might be different from the re sults which would have been obtained by using the a posteriori paramet er values. Hence, the sensitivity towards this a priori assumption was tested explicitly. For this purpose, the parameter space was sampled according to a Latin hypercube sampling scheme and the selection proce dure was applied in all sampling points as if these were a priori esti mates. From this extensive study it could be concluded that the result s of the procedure were not too severely influenced by the a priori as sumption on the parameter values. Therefore, the proposed procedure ap pears to be a powerful and practical tool for efficient and reliable m odel calibration. (C) 1997 IAWQ. Published by Elsevier Science Ltd.