Open Access
ARTICLE
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: .
Computers, Materials & Continua 2020, 65(1), 405-418. https://doi.org/10.32604/cmc.2020.010124
Received 12 February 2020; Accepted 17 May 2020; Issue published 23 July 2020
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.
Keywords
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.
Citations