Influence of a new discrete-time LQR-based motion cueing on driving simulator
Article dans une revue avec comité de lecture
This study proposes a method and an experimental validation to analyze dynamics response of the simulator's cabin and platform with respect to the type of the control used in the hexapod driving simulator. In this article, two different forms of motion platform tracking control are performed as a classical motion cueing algorithm and a discrete-time linear quadratic regulator (LQR) motion cueing algorithm. For each situation, vehicle dynamics and motion platform level data are registered from the driving simulation software. In addition, the natural frequencies of the roll accelerations are obtained in real-time by using FFT. The data are denoised by using wavelet 1D transformation. The results show that by using discrete-time LQR algorithm, the roll acceleration amplitudes that correspond to the natural frequencies and the total roll jerk have decreased at the motion platform level. Also, the natural frequencies have increased reasonably by using the discrete LQR motion cueing (1.5–2.2 Hz) compared with using the classical algorithm (0.4–1.5 Hz) at the motion platform, which is an indicator of motion sickness incidence avoidance. The literature shows that lateral motion (roll, yaw, etc.) in the frequency range of 0.1–0.5 Hz induces motion sickness. Furthermore, using discrete-time LQR motion cueing algorithm has decreased the sensation error (motion platform–vehicle (cabin) levels) two times in terms of total roll jerk. In conclusion, discrete-time LQR motion cueing has reduced the simulator sickness more than the classical motion cueing algorithm depending on sensory cue conflict theory.
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