Hybrid Dynamic Predictive Model for Rougher Flotation

Several dynamic models are able to represent the phenomenological behavior of flotation. On the other side, the interest in developing control strategies for large-scale processes has led to formulate novel methodologies which allow to consider the global performance of a plant, facilitating the design, validation and evaluation of more complex optimizing control strategies.In this work, we first develop a dynamic hybrid model for a flotation rougher circuit with one production line composed by four cell banks in series, connected by controlled valves. Each line is actuated by discrete valves, whose interaction with different bank pulp levels define several operating modes. The model was validated with data from an industrial plant.Subsequently, a hybrid prediction model is obtained by applying identification techniques to the different scenarios, valid for optimizing controller strategies. Our simulation results show that the proposed methodology is suitable for modelling the global behavior of a rougher flotation circuit, representing its nonlinear dynamic and providing a robust predictive models for several operating modes of the circuit.