CDGPS based identification of farm tractor steering effectiveness

Accurately modeling the relationship between the yaw rate and the steer angle of an off road vehicle is important when developing control laws for autonomous vehicle guidance. This relationship is a function of various factors such as vehicle configuration, loading, and ground conditions. A simple model was developed that accounted for time varying dependencies and a least-squares filter based on the LMS algorithm was created to identify this nonlinear dependence in real time. An autonomously guided farm tractor fitted with GPS based attitude measurement that is used for control system research served as the test platform. Excellent agreement was obtained between predicted steering effectiveness and measured steering effectiveness