Abstract

This work details the application of a multiple model approach to estimate frother concentration in flotation processes. The methodology consists of identifying a set of linear dynamic models representing the effect of gas rate on the collection-zone gas holdup at different known frother concentrations (calibration step). An adaptive law is then obtained using Bayes' rule to evaluate the conditional probability that each model represents the observed system behavior. In this way, a frother concentration estimate is calculated as a weighted sum of model probabilities and their associated (known) frother concentrations. Experimental results conducted in a two-phase system using Dowfroth250 are promising. Modeling and analysis for MIBC frother are also provided.