Evidence map›Paper›PMID 32456053›Full record

ArticleSensors (Basel, Switzerland)2020

An Intelligent Multi-Sensor Variable Spray System with Chaotic Optimization and Adaptive Fuzzy Control.

Lepeng Song, Jinpen Huang, Xianwen Liang, Simon X Yang, Wenjin Hu, Dedong Tang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Lepeng SongSchool of Electrical Engineering, Chongqing University of Science and Technology, Chongqing 401331, China.
Jinpen HuangSchool of Electrical Engineering, Chongqing University of Science and Technology, Chongqing 401331, China.
Xianwen LiangSchool of Electrical Engineering, Chongqing University of Science and Technology, Chongqing 401331, China.
Simon X YangSchool of Engineering, University of Guelph, Guelph, ON N1G 5H1, Canada.ORCID 0000-0002-6888-7993
Wenjin HuSchool of Electrical Engineering, Chongqing University of Science and Technology, Chongqing 401331, China.
Dedong TangSchool of Electrical Engineering, Chongqing University of Science and Technology, Chongqing 401331, China.

Funding

National Natural Science Foundation of China 61873043Natural Science Foundation of Chongqing cstc2018jcyjAX0336
6 · The paper itself

Abstract

During the variable spray process, the micro-flow control is often held back by such problems as low initial sensitivity, large inertia, large hysteresis, nonlinearity as well as the inevitable difficulties in controlling the size of the variable spray droplets. In this paper, a novel intelligent double closed-loop control with chaotic optimization and adaptive fuzzy logic is developed for a multi-sensor based variable spray system, where a Bang-Bang relay controller is used to speed up the system operation, and adaptive fuzzy nonlinear PID is employed to improve the accuracy and stability of the system. With the chaotic optimization of controller parameters, the system is globally optimized in the whole solution space. By applying the proposed double closed-loop control, the variable pressure control system includes the pressure system as the inner closed-loop and the spray volume system as the outer closed-loop. Thus, the maximum amount of spray droplets deposited on the plant surface may be achieved with the minimum medicine usage for plants. Multiple sensors (for example: three pressure sensors and two flow rate sensors) are employed to measure the system states. Simulation results show that the chaotic optimized controller has a rise time of 0.9 s, along with an adjustment time of 1.5 s and a maximum overshoot of 2.67% (in comparison using PID, the rise time is 2.2 s, the adjustment time is 5 s, and the maximum overshoot is 6.0%). The optimized controller parameters are programmed into the hardware to control the established variable spray system. The experimental results show that the optimal spray pressure of the spray system is approximately 0.3 MPa, and the flow rate is approximately 0.08 m

Indexed as

adaptive fuzzy controlchaos optimizationdata analysisdouble closed-loop controlmulti-sensor measurementvariable spray

Identifiers

PMID32456053
PMCPMC7285310

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.