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The Identification of the Wind Parameters Based on the Interactive Multi-Models

Lihua Zhu1, Zhiqiang Wu1, Lei Wang2, Yu Wang1, *

1 School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China.
2 School of Computing and Information Technology, University of Wollongong, Wollongong, NSW 2522, Australia.

* Corresponding Author: Yu Wang. Email: email.

Computers, Materials & Continua 2020, 65(1), 405-418. https://doi.org/10.32604/cmc.2020.010124

Abstract

The wind as a natural phenomenon would cause the derivation of the pesticide drops during the operation of agricultural unmanned aerial vehicles (UAV). In particular, the changeable wind makes it difficult for the precision agriculture. For accurate spraying of pesticide, it is necessary to estimate the real-time wind parameters to provide the correction reference for the UAV path. Most estimation algorithms are model based, and as such, serious errors can arise when the models fail to properly fit the physical wind motions. To address this problem, a robust estimation model is proposed in this paper. Considering the diversity of the wind, three elemental time-related Markov models with carefully designed parameter α are adopted in the interacting multiple model (IMM) algorithm, to accomplish the estimation of the wind parameters. Furthermore, the estimation accuracy is dependent as well on the filtering technique. In that regard, the sparse grid quadrature Kalman filter (SGQKF) is employed to comprise the computation load and high filtering accuracy. Finally, the proposed algorithm is ran using simulation tests which results demonstrate its effectiveness and superiority in tracking the wind change.

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Cite This Article

L. Zhu, Z. Wu, L. Wang and Y. Wang, "The identification of the wind parameters based on the interactive multi-models," Computers, Materials & Continua, vol. 65, no.1, pp. 405–418, 2020.

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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