Application of Fuzzy Logic and Approximate Reasoning to the Optimization of Sludge Dewatering

This paper presents a real-world application of approximate reasoning to sludge dewatering. One of the constraint is that the same rule base must be applicable in a network of heterogeneous wastewater treatment plants. In particular, they differ on how they are equipped of sensors or not. We propose a solution based on approximate reasoning to process both precise, i.e. measured instantly with an accurate sensor or with a delay of 24 hours in an analysis laboratory, and imprecise inputs, that come instantly from a low-cost sensor or even from human perception. We tested on a small model of a decanter centrifuge to study the behavior of the fuzzy inference system. The results are presented at the end of the paper and show that the fuzzy inference system tends to an optimal state even if the decanter centrifuge is disturbed.