LEARNING CONTROL OF AN AUTOGENOUS GRINDING CIRCUIT

This paper presents the results of the application of a new process control technique, the Learning Control, to a mineral processing operation. A hierarchical system of learning automata is used as a model of the controller. An empirical simulator capable of reproducing the dynamic of the autogenous grinding process is considered as the random environment in which the hierarchical system of automata operates. A probability distribution is associated to the manipulated variable. This distribution is continuously adjusted by the learning system using a reinforcement scheme. Numerical results have demonstrated its control properties, transparent tuning and robustness, while requiring minimal computational load.