Click on “Download PDF” for the PDF version or on the title for the HTML version. If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options. RULE-BASE REDUCTION FOR A FUZZY HUMAN OPERATOR PERFORMANCE MODELPublished by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org Citation: Applied Engineering in Agriculture. 22(4): 611-618. (doi: 10.13031/2013.21214) @2006Authors: W. R. Norris, Q. Zhang, R. S. Sreenivas Keywords: Human-in-the-loop design process, Fuzzy human operator performance model, Fuzzy control strategy, Fuzzy rule reduction This article presents a general procedure of reducing the number of fuzzy rules needed to perform a human-in-the-loop (HIL) design process using a virtual environment design tool. This HIL design process is created for designing an adaptive steering controller to achieve optimal vehicle maneuverability regardless of operators driving behaviors. In this design process, a dynamic model of an articulated off-road vehicle is implemented to determine the vehicle steering maneuverability via real-time simulation, and a virtual operator model is used to generate steer actions to guide the vehicle traveling on a predetermined path. Due to the complicated nature of steering an articulated vehicle, a high degree of granularity was required to cover all possible combinations of operating conditions. In order to meet real-time simulation requirements, a hierarchical fuzzy relations control strategy (FRCS) has been developed to reduce the size of the virtual operators rule-base. Using the developed hierarchy, the fuzzy steering controller could effectively incorporate the reduced size rule-base. Validation simulation showed that this hierarchical approach could reduce the size of the rule base by over 98% without affecting the performance of the virtual operator. (Download PDF) (Export to EndNotes)
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