With the increasing prevalence of high-order systems in engineering applications, these systems often exhibitsignificant disturbances and can be challenging to model accurately. As a result, the active disturbance rej...With the increasing prevalence of high-order systems in engineering applications, these systems often exhibitsignificant disturbances and can be challenging to model accurately. As a result, the active disturbance rejectioncontroller (ADRC) has been widely applied in various fields. However, in controlling plant protection unmannedaerial vehicles (UAVs), which are typically large and subject to significant disturbances, load disturbances andthe possibility of multiple actuator faults during pesticide spraying pose significant challenges. To address theseissues, this paper proposes a novel fault-tolerant control method that combines a radial basis function neuralnetwork (RBFNN) with a second-order ADRC and leverages a fractional gradient descent (FGD) algorithm.We integrate the plant protection UAV model’s uncertain parameters, load disturbance parameters, and actuatorfault parameters and utilize the RBFNN for system parameter identification. The resulting ADRC exhibits loaddisturbance suppression and fault tolerance capabilities, and our proposed active fault-tolerant control law hasLyapunov stability implications. Experimental results obtained using a multi-rotor fault-tolerant test platformdemonstrate that the proposed method outperforms other control strategies regarding load disturbance suppressionand fault-tolerant performance.展开更多
In order to solve the problems of insufficient training equipment,relatively lack of curriculum resources and single teaching means in the teaching of UAV(unmanned aerial vehicle)applied technology major,this paper st...In order to solve the problems of insufficient training equipment,relatively lack of curriculum resources and single teaching means in the teaching of UAV(unmanned aerial vehicle)applied technology major,this paper studies the application of MR(Mixed Reality)in UAV applied technology major teaching,with the teaching of UAV agriculture&forestry plant protection curriculum as the carrier.The study will solve the pain points in teaching,improve the teaching ability and teaching information level,and increase the talent training quality of UAV,agriculture&forestry plant protection and related majors.Furthermore,it will create a protective,interactive,remote and scalable teaching experience for stu-dents,which can improve the teaching effect and reduce the teaching cost.展开更多
In recent years,multi-rotor unmanned aerial vehicle(UAV)crop protection operations have experienced tremendous growth.Compared with manual operations,they have advantages such as high operational efficiency,small pest...In recent years,multi-rotor unmanned aerial vehicle(UAV)crop protection operations have experienced tremendous growth.Compared with manual operations,they have advantages such as high operational efficiency,small pesticide dosage,and low pesticide hazards for humans.However,the tiny droplets produced during UAV spraying for crop protection are affected by the rotor air flow and will drift in all directions in an uncontrollable manner,severely affecting the pesticide deposition pattern and resulting in pesticide waste.To improve pesticide use efficiency during multi-rotor UAV spraying,an electrostatic spray system was designed based on electrostatic spray technology and a six-rotor UAV.The proper operation parameters for the UAV electrostatic spray were determined by test,which were spray altitude of 50 cm above the crop,spray pressure of 0.3 MPa and charging voltage of 9 kV.Field test was performed based on these parameters.The results showed that compared with non-electrostatic spray,the electrostatic spray improved by 13.6%in the average deposition density above the sampling device and 32.6%in the middle.The research can provide a reference for designing multi-rotor UAV electrostatic spray devices.展开更多
基金the 2021 Key Project of Natural Science and Technology of Yangzhou Polytechnic Institute,Active Disturbance Rejection and Fault-Tolerant Control of Multi-Rotor Plant ProtectionUAV Based on QBall-X4(Grant Number 2021xjzk002).
文摘With the increasing prevalence of high-order systems in engineering applications, these systems often exhibitsignificant disturbances and can be challenging to model accurately. As a result, the active disturbance rejectioncontroller (ADRC) has been widely applied in various fields. However, in controlling plant protection unmannedaerial vehicles (UAVs), which are typically large and subject to significant disturbances, load disturbances andthe possibility of multiple actuator faults during pesticide spraying pose significant challenges. To address theseissues, this paper proposes a novel fault-tolerant control method that combines a radial basis function neuralnetwork (RBFNN) with a second-order ADRC and leverages a fractional gradient descent (FGD) algorithm.We integrate the plant protection UAV model’s uncertain parameters, load disturbance parameters, and actuatorfault parameters and utilize the RBFNN for system parameter identification. The resulting ADRC exhibits loaddisturbance suppression and fault tolerance capabilities, and our proposed active fault-tolerant control law hasLyapunov stability implications. Experimental results obtained using a multi-rotor fault-tolerant test platformdemonstrate that the proposed method outperforms other control strategies regarding load disturbance suppressionand fault-tolerant performance.
基金Supported by Vocational Education Reform and Innovation Project of Ministry of Education(HBKC217166,HBKC217168)Teaching Reform Project of Agricultural Specialty Teaching Steering Committee of Higher Vocational Education in Guangdong Province(YNYJZW2019YB09)+1 种基金Special Higher Vocational Enrollment Expansion Project of Teaching Reform Research and Practice Pro-ject in Guangdong Province(JGGZKZ2020141)Special Fund for Rural Revitalization Strategy of Huizhou in 2021(2021SC010502002)
文摘In order to solve the problems of insufficient training equipment,relatively lack of curriculum resources and single teaching means in the teaching of UAV(unmanned aerial vehicle)applied technology major,this paper studies the application of MR(Mixed Reality)in UAV applied technology major teaching,with the teaching of UAV agriculture&forestry plant protection curriculum as the carrier.The study will solve the pain points in teaching,improve the teaching ability and teaching information level,and increase the talent training quality of UAV,agriculture&forestry plant protection and related majors.Furthermore,it will create a protective,interactive,remote and scalable teaching experience for stu-dents,which can improve the teaching effect and reduce the teaching cost.
基金The authors acknowledge that the research was financially supported by National Key Technology Research and Development Program of the Ministry of Science and Technology of China(2014BAD06B01)Laboratory of Agricultural Mechanization Engineering Project(Provincial Key Laboratory).
文摘In recent years,multi-rotor unmanned aerial vehicle(UAV)crop protection operations have experienced tremendous growth.Compared with manual operations,they have advantages such as high operational efficiency,small pesticide dosage,and low pesticide hazards for humans.However,the tiny droplets produced during UAV spraying for crop protection are affected by the rotor air flow and will drift in all directions in an uncontrollable manner,severely affecting the pesticide deposition pattern and resulting in pesticide waste.To improve pesticide use efficiency during multi-rotor UAV spraying,an electrostatic spray system was designed based on electrostatic spray technology and a six-rotor UAV.The proper operation parameters for the UAV electrostatic spray were determined by test,which were spray altitude of 50 cm above the crop,spray pressure of 0.3 MPa and charging voltage of 9 kV.Field test was performed based on these parameters.The results showed that compared with non-electrostatic spray,the electrostatic spray improved by 13.6%in the average deposition density above the sampling device and 32.6%in the middle.The research can provide a reference for designing multi-rotor UAV electrostatic spray devices.
