A Motion Cueing Algorithm for A 2-DOF Pneumatic Motion Simulation Platform

A motion cueing algorithm (MCA) is proposed in this paper to simulate linear acceleration and angular velocity of vehicle on a two degrees of freedom (2-DOF) pneumatic motion simulation platform (PMSP). The MCA is consisting of data fusion algorithm and optimized low pass filter (LPF) with genetic algorithm (GA). Considering the thresholds of semicircular canal system models, two kinds of data fusion algorithms (DFAs) are designed to fusion linear acceleration and angular velocity into the desired angular trajectory of the platform. Moreover, LPF is used to remove the useless high-frequency information and reduce the impact of motion sensor white noise for getting smooth signals. Considering the body sense errors, GA is used to optimize low pass filter. Finally, the MCA is implemented by the MATLAB software, and the real experiment of simulating motion using active disturbance rejection controller (ADRC) is conducted on the PMSP. The effectiveness of the proposed algorithm is verified by the experiment results.