drift and then collect data instead the effect of the drift is deliberately introduced into the behavior of the mfc 22 by changing the mapping between the control input and the desired flow shown in fig2 a the data collected immediately after this change corresponds to a miscalibrated mfc 22 of all the data collected about 20 of it the 34 training set 34 is used by the learning system for the training phase and the remaining 34 test set 34 is used for testing the overall system using the training set selected features are extracted at step 512 from the calibrated and the miscalibrated mfc data in the illustrated embodiment valve voltage rise time and feedback error at step 513 a suitable clustering technique is used to form two clusters corresponding to the two classes calibrated and miscalibrated step 513 performed on a feature by feature basis at steps 514 and 515 the resulting hyper planes and centroids of each class are utilized for formulating the kb the final outcome of kb initialization phase 510 is a set of fuzzy logic rules to initialize the kb more specific details about feature selection and fuzzy rule development are provided below in.