Hierarchical Rule-Base Reduction Fuzzy Control for Path Tracking Variable Linear Speed Differential Steer Vehicles

Abstract

A novel waypoint navigation controller for a skid-steer vehicle is presented, where the controller is a multiple input-multiple output nonlinear angular velocity and linear speed controller. Hierarchical rule-base reduction was used in defining the controller. This entailed selecting inputs/outputs, determining the most globally influential inputs, generating a hierarchy relating inputs, selecting only the rules corresponding to the hierarchy, and, in effect, designing a symmetric rule-base. This dramatically reduced the rule-base size, by 97.7%, while maintaining global operating environment coverage. The stability analysis proved the asymptotic stability of the closed-loop controller-vehicle system. In addition, test courses were used to examine the effects of steering disturbance, phase lag, and overshoot as expressed in root mean square error (RMSE) and max error (ME). Outdoor experimental results for the controller's performance were contrasted with a benchmark waypoint navigation controller, pure pursuit, and a simpler implementation that only output linear speed. The controller was found to outperform the pure pursuit and simpler implementation experimentally by 72% and 50% in RMSE, 71% and 40% in ME, validating the controllers viability.