NEUROCONTROL OF A BALL MILL GRINDING CIRCUIT USING EVOLUTIONARY REINFORCEMENT LEARNING A. v. E. Conradie and C. Aldrich* Department of Chemical Engineering, University of Stellenbosch, Private Bag X1, Matieland, 7602, Stellenbosch, South Africa. Author to whom correspondence should be addressed: E-mail: CA1@ing.sun.ac.za ABSTRACT A ball mill grinding circuit is a nonlinear process characterised by significant process interaction, as a typical manipulated variable interacts with multiple controlled variables. To facilitate an accurate representation of the complex process dynamics, a rigorous ball mill grinding circuit is simulated. The dynamic model is used in its entirety for the development of a neurocontroller through the use of a novel evolutionary reinforcement learning algorithm, SANE (symbiotic, adaptive neuro-evolution). Reinforcement learning entails learning to achieve a desired control objective from direct cause-effect interactions with a simulated process plant. The SANE algorithm is able to implicitly learn to eliminate process interaction in the grinding circuit by taking a plant wide approach to controller design. The ability of the developed neurocontroller to maintain high performance in the presence of large disturbances in feed particle size distribution and ore hardness variations, is demonstrated. The generalisation afford by the SANE algorithm to the neurocontroller in dealing with considerable uncertainty in its operating environment attests to a large degree of controller autonomy. INTRODUCTION Ball mill grinding circuits are the primary unit operation in the production of metals from ore, as it precedes a concentration operation such as flotation. For the effective mineral concentration or subsequent mineral liberation, one of the foremost operational concerns of a grinding circuit is to provide an optimal particle size distribution to the flotation circuit. Another operational concern lies in the energy inefficiency of ore size reduction. With less than 10% of the electrical power input contributing to grinding of the ore, the total operating cost of a grinding facility may contribute significantly to the overall cost of mineral processing. To minimise operating cost it is thus pertinent that the ore feed rate remains in close proximity to the maximum design specification. This desirable operating state is constrained by the need to meet the particle size specification dictated