William John Shipman is researcher at MINTEK, working on machine learning applications within minerals processing and metallurgical plants. His main focus is on reinforcement learning at present. He have published a paper detailing some of this work in tuning proportional integral controllers. He have worked on an embedded model predictive control system for regulating cyanide dosing in a gold leaching circuit, developing the communications software, user interface, data collection and supporting software for the control system library (MINTEK proprietary library). His PhD in Engineering focused on analysing 3D X-ray micro-tomography images of ore samples to extract quantitative measurements. A large component of this work focused on applying machine learning to classifying voxels into mineral classes. His masters degree focused on modelling and controlling a miniature helicopter UAV. The model was developed from first principles and a number of experiments were designed to estimate the parameters of the model. Finally, a non-linear model predictive control system was developed in MATLAB and tested against a simulation of the helicopter UAV.
Brief Biography (English)
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