LEARNING CONTROL OF AN AUTOGENOUS GRINDING CIRCUIT

This paper presents the results of the application of a new process co ntrol technique, the Learning Control, to a mineral processing operati on. A hierarchical system of learning automata is used as a model of t he controller. An empirical simulator capable of reproducing the dynam ic of the autogenous grinding process is considered as the random envi ronment in which the hierarchical system of automata operates. A proba bility distribution is associated to the manipulated variable. This di stribution is continuously adjusted by the learning system using a rei nforcement scheme. Numerical results have demonstrated its control pro perties, transparent tuning and robustness, while requiring minimal co mputational load.