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 cure errors, simulation motion, and the distance of the adaptive parameters from their normal values. The newly developed adaptive algorithm use actuator states in the costs function rather than the tradition 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 decent algorithm. The step size is a function of simulator motion: large amounts of motion lead to a reduction in the steepest decent size. This reduction in step size eliminates a previously documented adaptive algorithm instability.

  • Corporate Authors:

    National Advanced Driving Simulator

    University of Iowa, 2401 Oakdale Boulevard
    Iowa City, IA  United States  52242-5003
  • Authors:
    • Grant, Peter R
    • Naseri, Asal
  • Conference:
  • Publication Date: 2005


  • English

Media Info

  • Media Type: CD-ROM
  • Features: References;
  • Pagination: 10p
  • Monograph Title: Driving Simulation Conference, North America 2005

Subject/Index Terms

Filing Info

  • Accession Number: 01140752
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Sep 28 2009 12:23PM