Optimal control for zinc solution purification based on interacting CSTR models

In zinc solution purification process, zinc dust is used to remove impurity ions in several serial stirred tank reactors. It is modelled by using several interacting continuously stirred tank reactor (ICSTR) systems with multiple time delays. Some unknown parameters of the ICSTR model are identified based on experimental data collected from a zinc production factory in China. Then a time delayed optimal control problem with continuous inequality constraints is constructed for the zinc solution purification. A numerical computational algorithm is developed, based on the control parameterization method, to design an optimal control law to ensure that a sufficiently low level of effluent impurities is achieved with the least zinc dust consumption. Finally, numerical simulation is carried out. The results obtained indicate that the effect of the optimal control for zinc solution purification is highly satisfactory.

► The CSTR model of each zinc solution purification reactor is established.
► A time-delayed dynamic model for the purification process was constructed.
► We identify the unknown model parameters based on the real-life observed data.
► A numerical method is developed based on the control parameterization method.
► The optimal control problem for purification is solved using the proposed method.