Abstract
Current methods to control the spraying quantity present several disadvantages, such as poor precision, a long adjustment time, and serious environmental pollution. In this paper, the flow control valve and the linear active disturbance controller (LADRC) were used to control the spraying quantity. Due to the disturbance characteristics in the spraying pipeline during the actual operation, the total disturbance was observed by a linear extended state observer (LESO). A 12 m commercial boom sprayer was used to carry out practical field operation tests after relevant intelligent transformation. The experimental results showed that the LADRC controller adopted in this paper can significantly suppress the disturbance in practical operation under three different operating speeds. Compared with the traditional proportional–integral–differential controller (PID) and an improved PID controller, the response speed of the proposed controller improved by approximately 3~5 s, and the steady-state error accuracy improved by approximately 2~9%.
Highlights
Pesticide spraying is still the main means of pest control in agricultural production in many countries
Radion 8140 (Teejet, IL, USA), PW-KZ1 (HuaiYu, Changzhou, China), and LC-19 (LiCheng, Ningbo, China) are the main spraying quantity control systems that are widely adopted in China
In the case of model uncertainty that exists in spraying quantity control systems, further research is needed on how to effectively use the model information and the intelligent methods to realize the online identification of flow valve model parameters
Summary
Pesticide spraying is still the main means of pest control in agricultural production in many countries. Many scholars have carried out mechanism analysis and modeling of spraying quantity regulation systems with different principles They developed relevant controllers and achieved certain research results. Shi and Liu et al [6,7] developed electromechanical control valves, respectively, and modeled them by mechanism analysis They adopted a fuzzy PID control algorithm in order to control the spraying quantity. In the case of model uncertainty that exists in spraying quantity control systems, further research is needed on how to effectively use the model information and the intelligent methods to realize the online identification of flow valve model parameters. The perturbation of the flow valve model parameters and external disturbance that occurred in the actual operation of the applicator was regarded as the total disturbance by the extended state observer, and the disturbance was compensated in real-time by the controller in order to achieve the purpose of restraining the disturbance.
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