Cuda-based technology for improving the efficiency of the aircraft motion

Authors

  • S. S. Tovkach National Aviation University

DOI:

https://doi.org/10.18372/1990-5548.50.11388

Keywords:

Graphics processing unit, multi-threaded, flight dynamics, adaptive motion control, wavelet analysis, turbulence flow, parallel computing

Abstract

Considered the method of parallel computing based on CUDA-architecture with detecting largeand small scale details of turbulence flow to adapt flight dynamics for motion control of the aircraft. Definedthe acceleration value of the parallel implementation relatively to series and the integraleffectiveness of parallel computing that allows to use the NVIDIA Tegra graphics processors toincrease the processing power of massively parallel calculations

Author Biography

S. S. Tovkach, National Aviation University

Candidate of Science (Engineering). Associate Professor. Automation and Energy Management Department

References

David A. Caughey, “Introduction to Aircraft Stability and Control.” Sibley School of Mechanical & Aerospace Engineering Cornell University. New York. 2011, 147 p.

Nairita Pal, Prasad Perlekar, Anupam Gupta, and Rahul Pandit “Binary-Fluid Turbulence: Signatures of Multifractal Droplet Dynamics and Dissipation Reduction” Indian Institute of Science. Bangalore, India. 2016, pp. 1–11.

T. Brandvik, and G. Pullan, “Acceleration of a 3D Euler solver using commodity graphics hardware,” 46th AIAA Aerospace Sciences Meeting and Exhibit, 2008.

E. Elsen, P. LeGresley, and E. Darve, “Large calculation of the flow over a hypersonic vehicle using a GPU,” Journal of Computational Physics, vol. 227, no. 24, 2008, pp. 10148–10161.

M. Farge, N.K.R. Kevlahan, V. Perrier, “Turbulence analysis, modelling and computing using wavelets” Laboratoire de Meteorologie Dynamique, Paris Cedex 5, 2009, pp. 1–66.

Parallel computing CUDA. [Online]. Available: http://www.nvidia.com.ua/object/cuda-parallel-computing-ru.html (in Russian).

Andrew Kerr, Gregory Diamos, Sudhakar Yalamanchili, “A Characterization and Analysis of PTX Kernels.” Georgia Institute of Technology, Atlanta, Georgia, 2013, pp. 1–10.

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How to Cite

Tovkach, S. S. (2016). Cuda-based technology for improving the efficiency of the aircraft motion. Electronics and Control Systems, 4(50), 58–62. https://doi.org/10.18372/1990-5548.50.11388

Issue

Vol. 4 No. 50 (2016)

Section

AUTOMATIC CONTROL SYSTEMS

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