MODEL PREDICTIVE MOTION CUEING ALGORITHM FOR A TRUCK SIMULATOR

摘要

The paper looks at the possibilities of applying a model predictive control (MPC) algorithm to control and optimize the motion cueing algorithm (MCA) employed in state-of-the-art simulators for the purposes of reproducing motion effects (in particular acceleration). Typically, MCAs feature a large number of parameters which need to be configured with respect to both the kinematic and dynamic limitations of the motion platform used and the human motion perception thresholds. When an MPC algorithm is employed, these constraints can be fully respected and the ultimate results can, at least in a sense, be considered optimal. The paper shows the possibilities of interlinking MPC with MCA to dynamically adjust the applicable constraints. In addition, all theoretical results will be verified by means of simulations. Since the research described in this paper has been conducted as part of an advanced truck simulator project pursued by the author the parameters chosen for all simulations respect the properties of the motion platform employed in this project.