Optimal race car motion cueing

This paper explores the application of numerical optimal control (NOC) to the synthesis of motion cueing algorithms for race-car simulators. These techniques are used to design washout filters that address the limitations of the commonly-employed linear quadratic Guassian (LQG) regulator and classical frequency shaping strategies. The primary disadvantage of the LQG and classical tuning methods is that they do not recognise explicitly the hardware limitations of the platform and thus have to rely on an iterative process to address workspace limitations. In two new algorithms a kinematic model of the platform is used to constrain explicitly the platform's motion within the available workspace. The first algorithm is directed to the optimisation of the parameters of a linear washout filter, while in the second approach the platform motion is governed by an open-loop optimal control. The results of the two new algorithms are tested on race-car minimum lap-time simulations, and then compared with a linear-optimal-control based solution. The race-car scenario presents different challenges from the passenger car and aircraft contexts; these differences are discussed.