Automatic control of a laboratory flotation column

The operation of industrial flotation columns requires the control of at le ast two variables, the interface position and the bias rate, by manipulatio n of some appropriate operating variables. Problems arise due to the reliab ility of existing methods of measuring the bias (i.e bias = tailings water - feed water), a situation which has often forced the industry to disregard this control loop. Moreover, when using such a measuring approach, the ide ntification of the process dynamics is impossible. A second problem arises from the possible interaction between both control loops that might call fo r the use of a more complex multivariable control strategy. Recent work done at Laval University has demonstrated the feasibility of an independent sensor for bias, which models the relation between the conduct ivity profile across the interface and the bias value using a neural networ k algorithm. A 250 cm height, 5.25 cm diameter Plexiglas laboratory column was equipped with a series of conductivity electrodes in its uppermost part (across the interface) to measure both interface position and bias rate. U sing such equipment, the flotation column dynamics was identified. The resu lts thus obtained permitted the design and implementation of a distributed PI control strategy, where bias was associated to wash water rate and froth depth to tails rate. Both PI controllers were tuned using a frequency-resp onse tuning method. Results of both identification and process control are presented and discussed. (C) 1999 Published by Elsevier Science Ltd. All ri ghts reserved.