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RULE-BASE REDUCTION FOR A FUZZY HUMAN OPERATOR PERFORMANCE MODEL

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Applied Engineering in Agriculture. Vol. 22(4): 611-618. (doi: 10.13031/2013.21214) @2006
Authors:   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.

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