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Stationary Random Vibration Analysis of Planetary-Wheeled Robotic Vehicle Based on Pseudo Excitation Method

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Abstract

Based on one planetary-wheeled robotic vehicle which lomotes on wild rough and loose terrain, a new 7 DOF spatial vibration model considering damping effect of wheel-terrain interaction is rebuilt, and the vibration differential equations are derived by the Lagrangian theory. The ride performances of this robotic vehicle are calculated accurately and efficiently by Pseudo Excitation Method (PEM) under two different approaches describing multi-points partial coherent stationary random excitation. The simulation results via MATLAB indicate that the responses characterized by corresponding Power Spectral Density (PSD) and root-mean-square (RMS) values are extraordinarily identical based on both the approach under the assumption of isotropy which describes the uneven road roughness and the approach using fitting coherent function which describes the uneven road excitation, while the previous approach is much more convenient than the latter one which is conventional, so we could have faith in the assumption of isotropy of uneven road excitations, under which a new approach to construct the PSD matrix of multi-points partial coherent stationary random excitation is established with simplicity and conveniency. In addition, the design parameters are reasonable as a result of the valid avoidance of the sensitive vibration region. The analytic expressions derived in the paper have a certain guiding significance in theoretical research of robotic vehicle vibration dynamics, vibration control and optimization of design parameters.

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Correspondence to Yuchuan Lu .

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Lu, Y., Su, B., Jiang, L. (2018). Stationary Random Vibration Analysis of Planetary-Wheeled Robotic Vehicle Based on Pseudo Excitation Method. In: Chen, Z., Mendes, A., Yan, Y., Chen, S. (eds) Intelligent Robotics and Applications. ICIRA 2018. Lecture Notes in Computer Science(), vol 10985. Springer, Cham. https://doi.org/10.1007/978-3-319-97589-4_23

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  • DOI: https://doi.org/10.1007/978-3-319-97589-4_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-97588-7

  • Online ISBN: 978-3-319-97589-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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