Research and Application of the Adaptive Agricultural Machinery Path Tracing Method Based on BP Neural Network

Скорочена інформація про документ
dc.contributor.authorGuojun Yan
dc.contributor.authorJianhua Gu
dc.contributor.authorNengjun Ben
dc.contributor.authorLili Wang
dc.date.accessioned2023-10-04T11:30:29Z
dc.date.available2023-10-04T11:30:29Z
dc.date.issued2017
dc.descriptionResearch and Application of the Adaptive Agricultural Machinery Path Tracing Method Based on BP Neural Network / Y. Guojun, G. Jianhua, B. Nengjun, W. Lili // Shipbuilding & Marine Infrastructure. – 2017. – № 1 (7). – P. 47–51.
dc.description.abstract1Advanced agricultural machinery and equipment is the basis for the realization of agricultural modernization. Aiming at the path tracking and the problem of control in the autonomous operation of intelligent agricultural machinery, this paper proposes an adaptive agricultural path tracking method based on BP neural network, which can realize the adaptive tracking of an agricultural machinery path. In this paper, the method is applied to the agricultural machinery with intelligent hydraulic brake control system to realize the path tracking experiment of the real vehicle; the straight path tracking and curve path tracking test are carried out for it. The test results show that the path tracking method designed in this paper can effectively improve the tracking accuracy. If compared to the classical PID control method, the precision of the straight path is improved by 12 % to 3 cm. The accuracy of the curve path is improved by 20 % to 6 cm. The algorithm designed in this paper has a high effectiveness and robustness, which is very important for improvement of the stability of agricultural machinery and the level of automatic navigation.
dc.identifier.issn2409-3858 (Print)
dc.identifier.issn2519-1845 (Online)
dc.identifier.urihttps://eir.nuos.edu.ua/handle/123456789/7091
dc.language.isoen
dc.titleResearch and Application of the Adaptive Agricultural Machinery Path Tracing Method Based on BP Neural Network
dc.typeArticle

Файли

Контейнер файлів
Зараз показуємо 1 - 1 з 1
Ескіз
Назва:
Guojun.pdf
Розмір:
703.92 KB
Формат:
Adobe Portable Document Format
Завантажити
Ліцензійна угода
Зараз показуємо 1 - 1 з 1
Ескіз недоступний
Назва:
license.txt
Розмір:
4.38 KB
Формат:
Item-specific license agreed upon to submission
Опис:
Завантажити

Зібрання

№1(7) 2017