The design of an automated froth flotation optimising control system, based on the maximisation of air recovery through air flowrate variation
Creators: name: Shean, Barry John
Publisher: name: Imperial College London
Year: 2012

description: Mineral froth flotation is one of the most broadly used separation methods in the mineral processing industry. Despite being introduced in the early 1900’s, and numerous years of research and development, flotation is still not fully understood and remains relatively inefficient. Consequently, large economic gains stand to be made through optimisation of present processes. Although numerous years of research into the automation of froth ﬂotation control have been conducted to increase process efficiency, options for advanced and/or optimising control systems remain limited. One proposed reason for this is the use of complicated and/or unclear control system goals; with many systems trying simultaneously to maximise the mineral recovery and concentrate grade (despite these two parameters being generally counter-correlated). However, the recent introduction of a new parameter – the air recovery – that gives an indication of the overall process performance, offers significant potential within flotation process control, as this is a single variable that can be measured rapidly online, and maximised. Moreover, it has been discovered that for flotation systems a peak in air recovery (or PAR) exists with increasing air flowrate, and that operating at this PAR air flowrate has metallurgical benefits. Thus, this PhD thesis aimed to develop and design an online PAR seeking control system that – for a single cell and through air flowrate manipulation – is able to drive the air flowrate towards the value that yields PAR (and hence the optimal operating conditions). This strategy represents a completely novel approach to flotation control, and is expected to have exciting industrial implications. The first step to achieving an online PAR seeking control system was the development of an online air recovery measurement system. This system – which makes use of air flowrate, froth velocity and froth height measurements – was trialled on both laboratory and industrial scale flotation systems, with good results being obtained. Subsequently, a review of numerical methods for the optimisation of ‘unknown objective functions’ – such as an air recovery curve – was conducted. This review highlighted a branch of methods known as ‘direct search methods’. Four of the more commonly known methods were integrated into PAR seeking control algorithms, and trialled on a model of the laboratory flotation system. These tests included starting below, above and at PAR, and also examined the effects of noise in the measured raw data and of disturbances to the air recovery curve. One method in particular, the Generating Set Search (or GSS) method, which is renowned for being simple, yet reliable and robust, was found to perform well under all conditions. This GSS-based PAR seeking control system was then tested experimentally on a laboratory flotation system. The results were again promising, with the control algorithm being found to handle noisy data, unstable conditions and large step change disturbances in the objective function. This good performance is largely attributed to the simple and non-assuming nature of the algorithm. It recommended that this GSS-based PAR seeking control system be trialled, and potentially implemented, on the industrial scale for the optimisation of flotation systems.