Optimal Motion Cueing for Race Cars

The application of optimal control to simulator motion cueing is examined. Existing motion cueing algorithms are hampered by the fact that they do not consider explicitly the optimal usage of simulator workspace. In this paper, numerical optimal control is used to minimize simulator platform acceleration errors, while explicitly recognizing the confines of the workspace. Actuator constraints are included and the impact of restricted actuator performance is thereby facilitated. The solution of open-loop optimal control calculations are also used as a baseline against which to compare the commonly employed linear quadratic Gaussian (LQG) and model predictive control-based techniques. The limitations of these methods are identified and two additional modules are introduced to the LQG algorithm to improve its performance.