Actuator State Based Adaptive Motion Drive Algorithm

A new Actuator State Based Adaptive (ASBA) motion drive algorithm was developed. In contrast to classical motion drive algorithms a subset of the motion drive parameters are time varying. The ASBA algorithm uses the steepest descent algorithm to adapt these parameters to minimize a pre-defined cost function. The cost function contains penalties on motion cue errors, simulator motion, and the distance of the adaptive parameters from their nominal values. The newly developed adaptive algorithm uses actuator states in the cost function rather than the traditional inertial Cartesian motion states. The ASBA algorithm is therefore able to adapt more “intelligently” to driving maneuvers that generate motion in multiple (Cartesian) degrees-of-freedom (such as a turn plus braking maneuver). The new adaptive motion drive algorithm also uses a variable step size in the steepest descent algorithm. The step size is a function of simulator motion: large amounts of motion lead to a reduction in the steepest descent step size. This reduction in step size eliminates a previously documented adaptive algorithm instability.