Traditional weather observation methods have limitations in detecting low-altitude,small-scale areas and sudden weather events.They often have insufficient coverage,slow response,or high costs.Multi-rotor unmanned aer...Traditional weather observation methods have limitations in detecting low-altitude,small-scale areas and sudden weather events.They often have insufficient coverage,slow response,or high costs.Multi-rotor unmanned aerial vehicles(UAVs),with their strong vertical take-off and landing ability,precise hovering,flexible movement,and ability to carry various small sensors,are gradually becoming key tools to fill these gaps and build three-dimensional weather observation networks.They show important value in medium-and small-scale weather monitoring and emergency weather support.This paper reviews the main sensors for multi-rotor weather drones,their operating modes,and key supporting technologies,summarizes the current state of technology,and provides references for future development.展开更多
This paper shows that the aerodynamic effects can be compensated in a quadrotor system by means of a control allocation approach using neural networks.Thus,the system performance can be improved by replacing the class...This paper shows that the aerodynamic effects can be compensated in a quadrotor system by means of a control allocation approach using neural networks.Thus,the system performance can be improved by replacing the classic allocation matrix,without using the aerodynamic inflow equations directly.The network training is performed offline,which requires low computational power.The target system is a Parrot MAMBO drone whose flight control is composed of PD-PID controllers followed by the proposed neural network control allocation algorithm.Such a quadrotor is particularly susceptible to the aerodynamics effects of interest to this work,because of its small size.We compared the mechanical torques commanded by the flight controller,i.e.,the control input,to those actually generated by the actuators and established at the aircraft.It was observed that the proposed neural network was able to closely match them,while the classic allocation matrix could not achieve that.The allocation error was also determined in both cases.Furthermore,the closed-loop performance also improved with the use of the proposed neural network control allocation,as well as the quality of the thrust and torque signals,in which we perceived a much less noisy behavior.展开更多
Manned multi-rotor electric Vertical Takeoff and Landing(eVTOL)aircraft is prone to actuator saturation due to its weak yaw control efficiency.To address this inherent problem,a rotor cross-tilt configuration is appli...Manned multi-rotor electric Vertical Takeoff and Landing(eVTOL)aircraft is prone to actuator saturation due to its weak yaw control efficiency.To address this inherent problem,a rotor cross-tilt configuration is applied in this paper,with an optimization method proposed to improve the overall control efficiency of the vehicle.First,a flight dynamics model of a 500-kg manned multi-rotor eVTOL aircraft is established.The accuracy of the co-axial rotor model is verified using a single arm test bench,and the accuracy of the flight dynamics model is verified by the flight test data.Then,an optimization method is designed based on the flight dynamics model to calculate an optimal rotor cross-tilt mounting angle,which not only improves the yaw control efficiency,but also basically maintains the efficiency of other control channels.The ideal rotor cross-tilt mounting angle for the prototype is determined by comprehensively considering the optimal results with different payloads,forward flight speeds,and rotor mounting angle errors.Finally,the feasibility of the rotor cross-tilt mounting angle is proved by analyzing the control derivatives of the flight dynamics model,the test data of a ground three Degree-of-Freedom(3DOF)platform,and the actual flight data of the prototype.The results show that a fixed rotor cross-tilt mounting angle can achieve ideal yaw control effectiveness,improving yaw angle tracking and hold ability,increasing endurance time,and achieving good yaw control performance with different payloads and forward speeds.展开更多
[Objective] The paper was to explore chemical control of Ceratovacuna lanigera Zehntner with multi-rotor unmanned aerial vehicle. [Method] According to the outbreak characteristics of C. lanigera,multi-rotor unmanned ...[Objective] The paper was to explore chemical control of Ceratovacuna lanigera Zehntner with multi-rotor unmanned aerial vehicle. [Method] According to the outbreak characteristics of C. lanigera,multi-rotor unmanned aerial vehicle was applied for flying control test. Referred to the spraying characteristics of multi-rotor unmanned aerial vehicle,two kinds of microcapsule pesticides,ALV-1501 and ALV-1502,and two kinds of spraying additives,SPA-01 and SPA-02,were designed to control C. lanigera. [Result] The control effect of ALV-1501 at the dose of 2. 25 L/hm;was 60. 02% at 1 d post administration and 54. 14%at 5 d post administration; the control effects of ALV-1502 at the dose of 2. 1 L/hm2 were 76. 35% and 81. 35% at 1 and 5 d post administration,respectively.Compared to individual pesticide,the control effects of ALV-1501 were improved 1. 42-1. 47 times and 1. 16-1. 14 times by adding 0. 6 L/hm;SPA-01 and SPA-02 in pesticide liquid,respectively. The control effects of ALV-1502 were improved 1. 23-1. 25 times and 1. 15-1. 16 times by adding 0. 6 L/hm2 SPA-01 and SPA-02,respectively. The control effects against C. lanigera at three flying speeds of 3,5 and 8 m/s were 99. 72%-99. 97%,81. 6%-99. 81% and63. 52%-68. 77%,respectively. [Conclusion]The results will provide a reference for application of multi-rotor unmanned aerial vehicle in prevention and control of C. lanigera in sugarcane field.展开更多
The propulsion systems of a multi-rotor unmanned aerial vehicle(UAV)is crucial,as it directly affects the UAV’s performance,efficiency,and safety.Since the components of the UAV propulsion system are highly interconn...The propulsion systems of a multi-rotor unmanned aerial vehicle(UAV)is crucial,as it directly affects the UAV’s performance,efficiency,and safety.Since the components of the UAV propulsion system are highly interconnectioned,we developed a fuzzy fault tree analysis method to analysis the varying reliability under different fault conditions.Combining the fuzzy fault tree analysis of the T-S model and the UAV propulsion system model,we constructed a fuzzy fault tree of the T-S type for the system and performed a reliability analysis.This fuzzy fault tree allows us to model the system from two perspectives:fuzzy failure rate and failure degree.Consequently,two methods can be used for failure analysis of UAV systems.The first method involves calculating the system’s fuzzy failure rate based on the component’s fuzzy failure rate.The second method calculates the fuzzy failure rate of the system based on the failure degree of the component.The computational results indicate that both methods are well-suited for fault diagnosis in UAV propulsion systems.Compared to traditional fault tree analysis,which does not subdivide fault degrees,the proposed methods provide more accurate fault rate assessments.展开更多
A nonlinear optimal(H-infinity)control method is developed for a wind power unit that comprises twin turbines,permanent magnet synchronous generators(PMSGs)and AC/DC converters.By proving differential flatness propert...A nonlinear optimal(H-infinity)control method is developed for a wind power unit that comprises twin turbines,permanent magnet synchronous generators(PMSGs)and AC/DC converters.By proving differential flatness properties for this system the associated setpoints definition problem is solved.The dynamic model of the wind power unit being initially expressed in a nonlinear and multivariable state-space form,undergoes approximate linearisation around a temporary operating point that is recomputed at each time-step of the control method.The linearisation relies on first-order Taylor series expansion and on the computation of the associated Jacobian matrices.For the linearised state-space model of the wind power unit,a stabilising optimal(H-infinity)feedback controller is designed.This controller stands for the solution to the nonlinear optimal control problem of the wind power unit under model uncertainty and external perturbations.To compute the controller's feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm.The global stability properties of the control method are proven through Lyapunov analysis.Finally,to implement state estimationbased control of the wind power unit,without the need to measure its entire state vector,the H-infinity Kalman Filter is used as a robust state estimator.展开更多
可垂直起降(vertical take-off and landing,VTOL)的多旋翼无人机姿态系统具有高度非线性、强耦合性特征,并且系统中存在的外界干扰和内部不确定性因素均会对多旋翼无人机飞行品质产生影响。为提高多旋翼无人机姿态控制的稳定性和鲁棒性...可垂直起降(vertical take-off and landing,VTOL)的多旋翼无人机姿态系统具有高度非线性、强耦合性特征,并且系统中存在的外界干扰和内部不确定性因素均会对多旋翼无人机飞行品质产生影响。为提高多旋翼无人机姿态控制的稳定性和鲁棒性,建立了外部干扰与内部不确定性因素共存的多旋翼无人机姿态系统,提出了基于改进的双闭环积分滑模的姿态自适应控制方法。通过仿真形式,验证了该系统能够稳定有效地执行姿态控制任务,并具有一定的抗干扰能力。文中所提出的方法可为无人机控制技术的发展提供一定的参考价值。展开更多
针对桥梁缺陷检测中存在的识别精度不足、嵌入式部署困难与系统集成度有限的问题,提出一种基于轻量化模型YOLOv5s与Transformer特征增强模块(C3TR)的无人机检测系统。方法上在YOLOv5s主干网络中引入C3TR,以融合全局注意力与局部卷积特征...针对桥梁缺陷检测中存在的识别精度不足、嵌入式部署困难与系统集成度有限的问题,提出一种基于轻量化模型YOLOv5s与Transformer特征增强模块(C3TR)的无人机检测系统。方法上在YOLOv5s主干网络中引入C3TR,以融合全局注意力与局部卷积特征,并设计STM32与Raspberry Pi 4B双主控架构,集成激光测距避障、图像拼接和可视化管理平台。实验结果表明:改进模型在总体数据集上的mAP@0.5达到0.718,Precision为80.4%,Recall为68.2%,较基线YOLOv5s分别提升11.5%、4.5%和2.3%;在Raspberry Pi 4B上实现端到端6~8 FPS的实时推理。与现有YOLOv4、YOLOv3等改进方法相比,本系统在保持轻量化的同时兼顾多类缺陷识别与工程化应用,验证了其在无人机嵌入式巡检中的可行性与实用价值。展开更多
The endurance performance(EP)of electric multi-rotors spraying drones(EMSDs)is a key technical indicator that ensures the completion of tasks and improves their usefulness.To improve the EP of current EMSD,a test syst...The endurance performance(EP)of electric multi-rotors spraying drones(EMSDs)is a key technical indicator that ensures the completion of tasks and improves their usefulness.To improve the EP of current EMSD,a test system was designed to determine the EP based on the EMSD test platform,and the performance evaluation method was studied.Firstly,a test model was established to determine the equivalent energy dissipation using the performance-testing platform of the EMSD.Secondly,a multisensory test system was constructed.An attitude sensor,high-power DC power supply,infrared thermal imager,and serial port server were selected.The mounting fixture was designed to meet the universal mounting requirements of drone.In addition,the software LabVIEW was employed to program the code for the controller and the host computer,where functions such as data collection,data processing,communication,and graphical user interface(GUI),were performed reliably in real time.Thirdly,the test method was explored by considering factors such as the power consumption,thermal efficiency ratio,and unit load power consumption rate.In particular,a comprehensive index method and expert consultation weight method were used to evaluate the EP of the EMSD with multiple indexes.Finally,a systematic real-machine test was carried out on the three types of drones that are currently widely used in the market.The results verified the effectiveness and feasibility of the proposed method,which was employed to test and evaluate the EP based on the EMSD performance testing platform.At the same time,it can provide a reference for the development of the EMSD.展开更多
基金supported by the High-Level Talent Foundation of Natural Science Research Funding Project for Ordinary Universities in Jiangsu Province(grant number.25KJD520004)Jinling Institute of Technology(grant number.JIT-B-202413).
文摘Traditional weather observation methods have limitations in detecting low-altitude,small-scale areas and sudden weather events.They often have insufficient coverage,slow response,or high costs.Multi-rotor unmanned aerial vehicles(UAVs),with their strong vertical take-off and landing ability,precise hovering,flexible movement,and ability to carry various small sensors,are gradually becoming key tools to fill these gaps and build three-dimensional weather observation networks.They show important value in medium-and small-scale weather monitoring and emergency weather support.This paper reviews the main sensors for multi-rotor weather drones,their operating modes,and key supporting technologies,summarizes the current state of technology,and provides references for future development.
文摘This paper shows that the aerodynamic effects can be compensated in a quadrotor system by means of a control allocation approach using neural networks.Thus,the system performance can be improved by replacing the classic allocation matrix,without using the aerodynamic inflow equations directly.The network training is performed offline,which requires low computational power.The target system is a Parrot MAMBO drone whose flight control is composed of PD-PID controllers followed by the proposed neural network control allocation algorithm.Such a quadrotor is particularly susceptible to the aerodynamics effects of interest to this work,because of its small size.We compared the mechanical torques commanded by the flight controller,i.e.,the control input,to those actually generated by the actuators and established at the aircraft.It was observed that the proposed neural network was able to closely match them,while the classic allocation matrix could not achieve that.The allocation error was also determined in both cases.Furthermore,the closed-loop performance also improved with the use of the proposed neural network control allocation,as well as the quality of the thrust and torque signals,in which we perceived a much less noisy behavior.
基金co-supported by the National Natural Science Foundation of China(Nos.12202406,11672128)。
文摘Manned multi-rotor electric Vertical Takeoff and Landing(eVTOL)aircraft is prone to actuator saturation due to its weak yaw control efficiency.To address this inherent problem,a rotor cross-tilt configuration is applied in this paper,with an optimization method proposed to improve the overall control efficiency of the vehicle.First,a flight dynamics model of a 500-kg manned multi-rotor eVTOL aircraft is established.The accuracy of the co-axial rotor model is verified using a single arm test bench,and the accuracy of the flight dynamics model is verified by the flight test data.Then,an optimization method is designed based on the flight dynamics model to calculate an optimal rotor cross-tilt mounting angle,which not only improves the yaw control efficiency,but also basically maintains the efficiency of other control channels.The ideal rotor cross-tilt mounting angle for the prototype is determined by comprehensively considering the optimal results with different payloads,forward flight speeds,and rotor mounting angle errors.Finally,the feasibility of the rotor cross-tilt mounting angle is proved by analyzing the control derivatives of the flight dynamics model,the test data of a ground three Degree-of-Freedom(3DOF)platform,and the actual flight data of the prototype.The results show that a fixed rotor cross-tilt mounting angle can achieve ideal yaw control effectiveness,improving yaw angle tracking and hold ability,increasing endurance time,and achieving good yaw control performance with different payloads and forward speeds.
基金Supported by Transformational Fund of Central Agricultural Scientific and Technological Achievements in China(2014GB2E000042)Special Fund of China Agricultural Industry Research System(CARS-20-2-1)
文摘[Objective] The paper was to explore chemical control of Ceratovacuna lanigera Zehntner with multi-rotor unmanned aerial vehicle. [Method] According to the outbreak characteristics of C. lanigera,multi-rotor unmanned aerial vehicle was applied for flying control test. Referred to the spraying characteristics of multi-rotor unmanned aerial vehicle,two kinds of microcapsule pesticides,ALV-1501 and ALV-1502,and two kinds of spraying additives,SPA-01 and SPA-02,were designed to control C. lanigera. [Result] The control effect of ALV-1501 at the dose of 2. 25 L/hm;was 60. 02% at 1 d post administration and 54. 14%at 5 d post administration; the control effects of ALV-1502 at the dose of 2. 1 L/hm2 were 76. 35% and 81. 35% at 1 and 5 d post administration,respectively.Compared to individual pesticide,the control effects of ALV-1501 were improved 1. 42-1. 47 times and 1. 16-1. 14 times by adding 0. 6 L/hm;SPA-01 and SPA-02 in pesticide liquid,respectively. The control effects of ALV-1502 were improved 1. 23-1. 25 times and 1. 15-1. 16 times by adding 0. 6 L/hm2 SPA-01 and SPA-02,respectively. The control effects against C. lanigera at three flying speeds of 3,5 and 8 m/s were 99. 72%-99. 97%,81. 6%-99. 81% and63. 52%-68. 77%,respectively. [Conclusion]The results will provide a reference for application of multi-rotor unmanned aerial vehicle in prevention and control of C. lanigera in sugarcane field.
文摘The propulsion systems of a multi-rotor unmanned aerial vehicle(UAV)is crucial,as it directly affects the UAV’s performance,efficiency,and safety.Since the components of the UAV propulsion system are highly interconnectioned,we developed a fuzzy fault tree analysis method to analysis the varying reliability under different fault conditions.Combining the fuzzy fault tree analysis of the T-S model and the UAV propulsion system model,we constructed a fuzzy fault tree of the T-S type for the system and performed a reliability analysis.This fuzzy fault tree allows us to model the system from two perspectives:fuzzy failure rate and failure degree.Consequently,two methods can be used for failure analysis of UAV systems.The first method involves calculating the system’s fuzzy failure rate based on the component’s fuzzy failure rate.The second method calculates the fuzzy failure rate of the system based on the failure degree of the component.The computational results indicate that both methods are well-suited for fault diagnosis in UAV propulsion systems.Compared to traditional fault tree analysis,which does not subdivide fault degrees,the proposed methods provide more accurate fault rate assessments.
文摘A nonlinear optimal(H-infinity)control method is developed for a wind power unit that comprises twin turbines,permanent magnet synchronous generators(PMSGs)and AC/DC converters.By proving differential flatness properties for this system the associated setpoints definition problem is solved.The dynamic model of the wind power unit being initially expressed in a nonlinear and multivariable state-space form,undergoes approximate linearisation around a temporary operating point that is recomputed at each time-step of the control method.The linearisation relies on first-order Taylor series expansion and on the computation of the associated Jacobian matrices.For the linearised state-space model of the wind power unit,a stabilising optimal(H-infinity)feedback controller is designed.This controller stands for the solution to the nonlinear optimal control problem of the wind power unit under model uncertainty and external perturbations.To compute the controller's feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm.The global stability properties of the control method are proven through Lyapunov analysis.Finally,to implement state estimationbased control of the wind power unit,without the need to measure its entire state vector,the H-infinity Kalman Filter is used as a robust state estimator.
文摘可垂直起降(vertical take-off and landing,VTOL)的多旋翼无人机姿态系统具有高度非线性、强耦合性特征,并且系统中存在的外界干扰和内部不确定性因素均会对多旋翼无人机飞行品质产生影响。为提高多旋翼无人机姿态控制的稳定性和鲁棒性,建立了外部干扰与内部不确定性因素共存的多旋翼无人机姿态系统,提出了基于改进的双闭环积分滑模的姿态自适应控制方法。通过仿真形式,验证了该系统能够稳定有效地执行姿态控制任务,并具有一定的抗干扰能力。文中所提出的方法可为无人机控制技术的发展提供一定的参考价值。
文摘针对桥梁缺陷检测中存在的识别精度不足、嵌入式部署困难与系统集成度有限的问题,提出一种基于轻量化模型YOLOv5s与Transformer特征增强模块(C3TR)的无人机检测系统。方法上在YOLOv5s主干网络中引入C3TR,以融合全局注意力与局部卷积特征,并设计STM32与Raspberry Pi 4B双主控架构,集成激光测距避障、图像拼接和可视化管理平台。实验结果表明:改进模型在总体数据集上的mAP@0.5达到0.718,Precision为80.4%,Recall为68.2%,较基线YOLOv5s分别提升11.5%、4.5%和2.3%;在Raspberry Pi 4B上实现端到端6~8 FPS的实时推理。与现有YOLOv4、YOLOv3等改进方法相比,本系统在保持轻量化的同时兼顾多类缺陷识别与工程化应用,验证了其在无人机嵌入式巡检中的可行性与实用价值。
基金We acknowledge that this research work was financially supported by the Science and Technology Plan of Guangdong Province of China(Project No.2014A020208103,2015B020206003,2017B090903007)Innovative Research Team of Guangdong Province Agriculture Research System(2017LM2153)for funding this research.
文摘The endurance performance(EP)of electric multi-rotors spraying drones(EMSDs)is a key technical indicator that ensures the completion of tasks and improves their usefulness.To improve the EP of current EMSD,a test system was designed to determine the EP based on the EMSD test platform,and the performance evaluation method was studied.Firstly,a test model was established to determine the equivalent energy dissipation using the performance-testing platform of the EMSD.Secondly,a multisensory test system was constructed.An attitude sensor,high-power DC power supply,infrared thermal imager,and serial port server were selected.The mounting fixture was designed to meet the universal mounting requirements of drone.In addition,the software LabVIEW was employed to program the code for the controller and the host computer,where functions such as data collection,data processing,communication,and graphical user interface(GUI),were performed reliably in real time.Thirdly,the test method was explored by considering factors such as the power consumption,thermal efficiency ratio,and unit load power consumption rate.In particular,a comprehensive index method and expert consultation weight method were used to evaluate the EP of the EMSD with multiple indexes.Finally,a systematic real-machine test was carried out on the three types of drones that are currently widely used in the market.The results verified the effectiveness and feasibility of the proposed method,which was employed to test and evaluate the EP based on the EMSD performance testing platform.At the same time,it can provide a reference for the development of the EMSD.
