A Soft Computing Approach to Controlling Emissions Under Imperfect Sensors

NOx emissions from commercial equipment vehicles can be controlled by the introduction of cleansing agents into output of the equipment. This process requires a monitoring of the output by sensors. Typically, these sensors can be of two types, physical and virtual, each of which can be imperfect in their readings. Physical sensors gradually deteriorate in time while virtual sensors have limit range of reliability. We provide an approach for fusing these imperfect sensor readings using the ordered weighted averaging (OWA) operator. The use of the OWA operator allows users to easily provide their preferred tradeoff between costly introductions of too much cleansing agent versus the possibility of penalization for emission violation. We also provide a methodology for determining the state of the physical sensor. We observe that the system described in this paper has been operationally implemented.