Issue |
Mechanics & Industry
Volume 24, 2023
|
|
---|---|---|
Article Number | 30 | |
Number of page(s) | 17 | |
DOI | https://doi.org/10.1051/meca/2023025 | |
Published online | 28 August 2023 |
Regular Article
Improved fuzzy neural network control for the clamping force of Camellia fruit picking manipulator
College of Mechanical and Electrical Engineering, Central South University of Forestry and Technology, Changsha 410000, China
* e-mail: junlili1122@163.com
Received:
19
May
2022
Received in final form:
22
April
2023
Accepted:
9
July
2023
During the operation of the vibrating mechanism, the push-shaking camellia fruit picking manipulator needs to ensure a constant force output of the clamping hydraulic motor in order to make sure that the camellia fruit tree trunk wouldn't loosen or damage, which may affect its later growth, during the picking process. In this regard, this paper derived the state space model of the valve-controlled clamping hydraulic motor system of the push-shaking camellia fruit picking manipulator, and the fuzzy wavelet neural network (FWNN) was designed on the basis of the traditional incremental PID control principle and the parameters of the neural network were optimized by the improved grey wolf optimizer (GWO). And then, the control system was simulated with the MATLAB/Simulink software without and with external interference, and compared and analyzed it with traditional PID controller and fuzzy PID (FPID) controller. The results show that the traditional PID controller and the FPID control have slow response and poor robustness, while the improved fuzzy wavelet neural network PID (IFWNN PID) controller possesses the characteristics of fast response and strong robustness, which can well meet the requirement of the constant clamping force of hydraulic motors. Finally, the field clamping test was carried out on the picking manipulator. The results show that the manipulator controlled by the IFWNN PID controller shortens the clamping time by 20.0% and reduces the clamping damage by 13.6% compared with the PID controller, which is verified that the designed controller can meet the clamping operation requirements of the camellia fruit picking machine.
Key words: Camellia fruit picking manipulator / clamping force PID control / fuzzy wavelet neural network / improved grey wolf optimization algorithm
© Z.F. Fan et al., Published by EDP Sciences 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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