Abstract

Model-based control strategies rely heavily on precise models to make accurate predictions. In mineral processing, particularly, due to complexities such as strong nonlinearities, variable coupling, time varying parameters, etc.; the development of accurate process models becomes an increasingly difficult task. Additionally, the ability to simulate process behavior without having to disturb plant operation prevents the loss of man-hours and production. Furthermore, current control solutions favor the use of linearized models and rely on expert systems to handle discrete variables such as discrete valves, signaling lights and tripper cars. Controllers that do not take into account the operation of these discrete variables may exhibit a suboptimal performance. For the previous reason, it is of special interest the design and development of controllers based on hybrid models, which incorporate both continuous and discrete variables in an unified model. This paper describes the modeling and simulation of the main processes of a hydrometallurgical plant, followed by the hybrid model identification of its crushing circuit. Simulation results of the response of the identified models are compared to the response of a nonlinear simulator, calibrated with real plant data, to qualitatively validate the models developed. The hybrid models identified in this manner are used for the design and development of hybrid controllers for the crushing plant. Simulation results show that the hybrid controllers exhibit a better performance when compared to a basic control scheme.