A novel structure of vehicle motion cueing algorithm for a pneumatic motion simulation platform

Abstract

In this paper, a novel structure of motion cueing algorithm (MCA) is proposed to simulate translational accelerations and angular velocities of vehicles on a pneumatic motion simulation platform (PMSP). The designed MCA includes nonlinear scaling algorithm, linear quadraticregulator (LQR), low pass filter and data fusion algorithm.Taking into account absolute sensory thresholds of human vestibular organ, the nonlinear scaling algorithm is designed to scale the translational accelerations and angular velocities of vehicles for ensuring the outputs of the MCA are inangular displacement ranges of the PMSP. According to the model of otolith organ and semicirular canal, the LQR ispresented to constrain the perception errors between the vehicles and PMSP. The data fusion algorithm is proposed to obtain desired angular displacement of the PMSP from the outputs of the nonlinear scaling algorithm for reducing perception errors. Considering the ranges of deflection angleand angular velocity on the PMSP, perception errors and absolute sensory thresholds, gains of the MCA are optimized by genetic algorithm. Note that the designed MCA can notonly be applied to the PMSP, but also be extended to the classical 6-degree-of-freedom platform for improving simulation performance. Finally, the effectiveness of the proposed algorithm is verified by real experiment using an active disturbance rejection controller.