scholarly journals Design of and Experiment with Seedling Selection System for Automatic Transplanter for Vegetable Plug Seedlings

Agronomy ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 2031
Author(s):  
Yongshuang Wen ◽  
Leian Zhang ◽  
Xuemei Huang ◽  
Ting Yuan ◽  
Junxiong Zhang ◽  
...  
Keyword(s):  
Pid Control ◽  
Control Algorithm ◽  
Seedling Survival ◽  
Conveyor Belt ◽  
Identification System ◽  
Selection System ◽  
Success Rates ◽  
Fuzzy Pid Control ◽  
Plug Seedling ◽  
Adaptive Fuzzy Pid Control

In the process of vegetable plug seedling cultivation, packaging, and transportation, there may be missing, unhealthy or injured seedlings in the tray, which results in a missed planting or a low seedling survival rate after automatic transplanting. In this study, a seedling selection system with the function of seedlings identification, week seedlings elimination, and missing seedlings supplement was developed for an automatic transplanter. A plug seedling identification system based on a machine vision was used to detect vegetable plug seedlings based on the area characteristics of plug seedlings, stem leaves and plug bodies. The identification results were transmitted to a programmable logic controller (PLC), which controlled a nozzle to eliminate the unqualified seedlings from the conveyor belt lattice. When the empty conveyor belt lattice reaches the seedling throwing funnel, the rear conveyor belt lattice with the plug seedling is accelerated to ensure the continuity of seedlings supply. The adaptive fuzzy PID control algorithm was used to control the stepper motor of the conveyor belt to realize accurate seedling conveying and a seedling supplement. Using 30 days pepper plug seedlings as experimental seedlings, a comparative field experiment was carried out to evaluate the performance of the seedling selection system. The results showed that when the seedling selection system was turned on and the seedling extracting frequencies were 60, 80, and 100 plants/min, the success rates of plug seedling identification were 98.84%, 98.38%, and 96.99%, and the robust seedling rates were 98.05%, 97.78%, and 95.83%. The robust seedling rates were increased by 15.64%, 16.07%, and 13.89%, respectively, in contrast to turning off the seedling selection system.

Research on Signal of Branch Junction Based on Adaptive Fuzzy-PID Control

2011 ◽  
Vol 135-136 ◽  
pp. 809-813
Author(s):  
Yong Feng Ju ◽  
Le Zhao ◽  
Shang Gao
Keyword(s):  
Pid Control ◽  
Control Algorithm ◽  
Simulation Analysis ◽  
Rapid Development ◽  
Urban Traffic ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Adaptive Fuzzy ◽  
Big City ◽  
Adaptive Fuzzy Pid Control

With the rapid development of the urbanization, the problem of city transportation has been becoming the same issue to each big city in China. As the converge points of urban traffic, the branch junctions are playing important role in the road net and traffic flow. It is true that traditional PID control algorithm is widely used in various control systems. Because its principle is simple and easy to build and has no error in the steady state, etc. However, it does not have a good adaptability towards the change of parameters. It is inferior towards interference, etc. According to the above situation, a adaptive Fuzzy-PID control algorithm is proposed which has returned the characters of regular PID control algorithm. The fuzzy control algorithm is used to realize the on-line regulating relative PID parameters. The simulation analysis indicates that the presented method is effective to improve the main road control.

Robust Control Method Based on Machine Learning for Boiler Combustion System

2014 ◽  
Vol 685 ◽  
pp. 368-372 ◽  
Author(s):  
Hao Zhang ◽  
Ya Jie Zhang ◽  
Yan Gu Zhang
Keyword(s):  
Robust Control ◽  
Intelligent Control ◽  
Pid Control ◽  
Control Algorithm ◽  
Control Method ◽  
Support Vector ◽  
Control Performance ◽  
Fuzzy Pid Control ◽  
On Line ◽  
Control Output

In this study, we presented a boiler combustion robust control method under load changes based on the least squares support vector machine, PID parameters are on-line adjusted and identified by LSSVM, optimum control output is obtained. The simulation result shows control performance of the intelligent control algorithm is superior to traditional control algorithm and fuzzy PID control algorithm, the study provides a new control method for strong non-linear boiler combustion control system.

The research on visual industrial robot which adopts fuzzy PID control algorithm

2017 ◽  
Author(s):  
Yifei Feng ◽  
Guoping Lu ◽  
Lulin Yue ◽  
Weifeng Jiang ◽  
Ye Zhang
Keyword(s):  
Pid Control ◽  
Control Algorithm ◽  
Industrial Robot ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control

scholarly journals Research on Intelligent Control System of Thermal Print Head Based on FPGA

2021 ◽  
Author(s):  
Yang Xu ◽  
Sheng Wang ◽  
Ying Peng
Keyword(s):  
Pid Control ◽  
Control Algorithm ◽  
Control Method ◽  
Print Quality ◽  
Fuzzy Pid ◽  
Single Chip ◽  
Fuzzy Pid Control ◽  
Print Head ◽  
Field Programmable ◽  
Time Required

Thermal print head heating realtime temperature fluctuations are too large, often causing damage to the print head heating point, resulting in poor print quality and unsatisfactory print results. Therefore, in order to improve the stability of the thermal print head during printing, and at the same time solve the inefficiency of the traditional single chip microcomputer control of the thermal print head heating method, a field programmable gate array (FPGA) based thermal print head heating control method is proposed. In order to control the core, the intelligent fuzzy PID control algorithm is used to ensure that the temperature of the print head can be stabilized quickly. Through simulation and experimental verification, it is shown that the intelligent fuzzy PID control algorithm greatly improves the temperature stabilization effect, and the time required to reach stability short, not only improve the printing accuracy, but also extend the life of the print head.

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