Multiobjective tuning technique for MPC in grinding circuits

We investigate the control challenges in grinding circuits---slow dynamics, long dead times, variable coupling--- and the controller tuning challenge, that is, the difficulty in translating operating goals into tuning goals and closed-loop performance. A tuning algorithm for DMC (dynamic matrix control), suitable for the mineral processing industry, is proposed. The tuning problem is posed as a multiobjective optimization problem, in which the tuning goals are directly related to the desired closed-loop performance of process variables. The problem is solved using a compromise optimization, which minimizes the Euclidian distance between a feasible solution and the Utopia solution. Three case studies are presented, which validate the tuning algorithm for DMC in linear and non-linear grinding circuit models. The closed-loop performance obtained with the proposed tuning algorithm is compared to the one obtained through a benchmark tuning technique from the literature. The proposed tuning method has the following features: i) it shapes the closed-loop response according to the goal definitions for linear systems; ii) it requires tailored initial guesses and search spaces to converge to a stabilizing solution in non-linear applications; and iii) it allows the user to specify the desired closed-loop performance behavior in the tuning procedure, allowing the implementation of an adequate controller for each situation.