Development Of Fuzzy Rule-Based Systems For Industrial Flotation Plants By Use Of Inductive Techniques And Genetic Algorithms

Control of flotation processes is mostly managed by plant operators, who assess the performance of the plant based on their own experience and other heuristic rules. These rules tend to be subjective or ill-defined, since most of them are concerned with the structure of the flotation froth, such as colour, bubble size and shape distributions, froth mobility and froth stability. These phenomena are very difficult to quantify objectively, and inexperience on the part of the operators, human error, etc., can lead to significant inefficiencies in plant operation. In this paper the development of a fuzzy system to support the control decisions of plant operators is described, which leads to significantly smoother control action and more stable plant operation than could be obtained with crisp sets of rules or manual control strategies. Keywords: flotation, fuzzy logic, image analysis, genetic algorithms, rule induction