This paper discusses the design and software-in-theloop implementation of adaptive formation controllers for fixedwing unmanned aerial vehicles(UAVs) with parametric uncertainty in their structure, namely uncertain ma...This paper discusses the design and software-in-theloop implementation of adaptive formation controllers for fixedwing unmanned aerial vehicles(UAVs) with parametric uncertainty in their structure, namely uncertain mass and inertia. In fact, when aiming at autonomous flight, such parameters cannot assumed to be known as they might vary during the mission(e.g.depending on the payload). Modeling and autopilot design for such autonomous fixed-wing UAVs are presented. The modeling is implemented in Matlab, while the autopilot is based on ArduPilot, a popular open-source autopilot suite. Specifically, the ArduP ilot functionalities are emulated in Matlab according to the Ardupilot documentation and code, which allows us to perform software-in-the-loop simulations of teams of UAVs embedded with actual autopilot protocols. An overview of realtime path planning, trajectory tracking and formation control resulting from the proposed platform is given. The software-inthe-loop simulations show the capability of achieving different UAV formations while handling uncertain mass and inertia.展开更多
针对目前智能网联汽车测试软件在环测试环节尚未成熟的问题,提出一种基于SUMO的智能网联汽车测试环境。上述测试环境依托交通流仿真软件SUMO(Simulation of Urban Mobility)平台,使用MATLAB/Simulink对车辆动力学进行仿真;使用罗技方向...针对目前智能网联汽车测试软件在环测试环节尚未成熟的问题,提出一种基于SUMO的智能网联汽车测试环境。上述测试环境依托交通流仿真软件SUMO(Simulation of Urban Mobility)平台,使用MATLAB/Simulink对车辆动力学进行仿真;使用罗技方向盘与Simulink采集驾驶员操作信息;在Unity3D中与SUMO同步环境场景并实现3D视觉效果。使用虚拟驾驶设备和联合汽车电子公司成熟的智能网联功能对环境进行了验证,结果表明,新开发的测试系统建立的虚拟车辆可以遵循驾驶员驾驶意图,同时能够给通用智能网联汽车软件提供软件在环测试环境,进行模块化测试,测试结果准确,试验数据可靠,整套系统反应灵敏、操作安全、沉浸感较强。展开更多
Robustness testing for safety-critical embedded software is still a challenge in its nascent stages. In this paper, we propose a practical methodology and implement an environment by employing model-based robustness t...Robustness testing for safety-critical embedded software is still a challenge in its nascent stages. In this paper, we propose a practical methodology and implement an environment by employing model-based robustness testing for embedded software systems. It is a system-level black-box testing approach in which the fault behaviors of embedded software is triggered with the aid of modelbased fault injection by the support of an executable model-driven hardware-in-loop （HIL） testing environment. The prototype implementation of the robustness testing environment based on the proposed approach is experimentally discussed and illustrated by industrial case studies based on several avionics-embedded software systems. The results show that our proposed and implemented robustness testing method and environment are effective to find more bugs, and reduce burdens of testing engineers to enhance efficiency of testing tasks, especially for testing complex embedded systems.展开更多
In wheel–rail adhesion studies,most of the test rigs used are simplified designs such as a single wheel or wheelset,but the results may not be accurate.Alternatively,representing the complex system by using a full ve...In wheel–rail adhesion studies,most of the test rigs used are simplified designs such as a single wheel or wheelset,but the results may not be accurate.Alternatively,representing the complex system by using a full vehicle model provides accurate results but may incur complexity in design.To trade off accuracy over complexity,a bogie model can be the optimum selection.Furthermore,only a real-time model can replicate its physical counterpart in the time domain.Developing such a model requires broad expertise and appropriate software and hardware.A few published works are available which deal with real-time modeling.However,the influence of the control system has not been included in those works.To address these issues,a real-time scaled bogie test rig including the control system is essential.Therefore,a 1:4 scaled bogie roller rig is developed to study the adhesion between wheel and roller contact.To compare the performances obtained from the scaled bogie test rig and to expand the test applications,a numerical simulation model of that scaled bogie test rig is developed using Gensys multibody software.This model is the complete model of the test rig which delivers more precise results.To exactly represent the physical counterpart system in the time domain,a real-time scaled bogie test rig(RT-SBTR)is developed after four consecutive stages.Then,to simulate the RT-SBTR to solve the internal state equations and functions representing the physical counterpart system in rigs used are simplified designs such as a single wheel or wheelset,but the results may not be accurate.Alternatively,representing the complex system by using a full vehicle model provides accurate results but may incur complexity in design.To trade off accuracy over complexity,a bogie model can be the optimum selection.Furthermore,only a real-time model can replicate its physical counterpart in the time domain.Developing such a model requires broad expertise and appropriate software and hardware.A few published works are available which deal with rea展开更多
基金supported by the Fundamental Research Funds for the Central Universities(4007019109)(RECON-STRUCT)the Special Guiding Funds for Double First-class(4007019201)the Joint TU Delft-CSSC Project ‘Multi-agent Coordination with Networked Constraints’(MULTI-COORD)
文摘This paper discusses the design and software-in-theloop implementation of adaptive formation controllers for fixedwing unmanned aerial vehicles(UAVs) with parametric uncertainty in their structure, namely uncertain mass and inertia. In fact, when aiming at autonomous flight, such parameters cannot assumed to be known as they might vary during the mission(e.g.depending on the payload). Modeling and autopilot design for such autonomous fixed-wing UAVs are presented. The modeling is implemented in Matlab, while the autopilot is based on ArduPilot, a popular open-source autopilot suite. Specifically, the ArduP ilot functionalities are emulated in Matlab according to the Ardupilot documentation and code, which allows us to perform software-in-the-loop simulations of teams of UAVs embedded with actual autopilot protocols. An overview of realtime path planning, trajectory tracking and formation control resulting from the proposed platform is given. The software-inthe-loop simulations show the capability of achieving different UAV formations while handling uncertain mass and inertia.
文摘针对目前智能网联汽车测试软件在环测试环节尚未成熟的问题,提出一种基于SUMO的智能网联汽车测试环境。上述测试环境依托交通流仿真软件SUMO(Simulation of Urban Mobility)平台,使用MATLAB/Simulink对车辆动力学进行仿真;使用罗技方向盘与Simulink采集驾驶员操作信息;在Unity3D中与SUMO同步环境场景并实现3D视觉效果。使用虚拟驾驶设备和联合汽车电子公司成熟的智能网联功能对环境进行了验证,结果表明,新开发的测试系统建立的虚拟车辆可以遵循驾驶员驾驶意图,同时能够给通用智能网联汽车软件提供软件在环测试环境,进行模块化测试,测试结果准确,试验数据可靠,整套系统反应灵敏、操作安全、沉浸感较强。
基金the Aeronautics Science Foundation of China(No.2011ZD51055)Science and Technology on Reliability&Environmental Engineering Laboratory(No.302367)the National Pre-Research Foundation of China(No.51319080201)
文摘Robustness testing for safety-critical embedded software is still a challenge in its nascent stages. In this paper, we propose a practical methodology and implement an environment by employing model-based robustness testing for embedded software systems. It is a system-level black-box testing approach in which the fault behaviors of embedded software is triggered with the aid of modelbased fault injection by the support of an executable model-driven hardware-in-loop （HIL） testing environment. The prototype implementation of the robustness testing environment based on the proposed approach is experimentally discussed and illustrated by industrial case studies based on several avionics-embedded software systems. The results show that our proposed and implemented robustness testing method and environment are effective to find more bugs, and reduce burdens of testing engineers to enhance efficiency of testing tasks, especially for testing complex embedded systems.
基金The authors greatly appreciate the financial support from the Rail Manufacturing Cooperative Research Centre(funded jointly by participating rail organizations and the Australian Federal Government’s Business Cooperative Research Centres Program)through Project R1.7.1-“Estimation of adhesion conditions between wheels and rails for the development of advanced braking control systems.”Tim McSweeney,Adjunct Research Fellow,Centre for Railway Engineering is thankfully acknowledged for his assistance with proofreading.
文摘In wheel–rail adhesion studies,most of the test rigs used are simplified designs such as a single wheel or wheelset,but the results may not be accurate.Alternatively,representing the complex system by using a full vehicle model provides accurate results but may incur complexity in design.To trade off accuracy over complexity,a bogie model can be the optimum selection.Furthermore,only a real-time model can replicate its physical counterpart in the time domain.Developing such a model requires broad expertise and appropriate software and hardware.A few published works are available which deal with real-time modeling.However,the influence of the control system has not been included in those works.To address these issues,a real-time scaled bogie test rig including the control system is essential.Therefore,a 1:4 scaled bogie roller rig is developed to study the adhesion between wheel and roller contact.To compare the performances obtained from the scaled bogie test rig and to expand the test applications,a numerical simulation model of that scaled bogie test rig is developed using Gensys multibody software.This model is the complete model of the test rig which delivers more precise results.To exactly represent the physical counterpart system in the time domain,a real-time scaled bogie test rig(RT-SBTR)is developed after four consecutive stages.Then,to simulate the RT-SBTR to solve the internal state equations and functions representing the physical counterpart system in rigs used are simplified designs such as a single wheel or wheelset,but the results may not be accurate.Alternatively,representing the complex system by using a full vehicle model provides accurate results but may incur complexity in design.To trade off accuracy over complexity,a bogie model can be the optimum selection.Furthermore,only a real-time model can replicate its physical counterpart in the time domain.Developing such a model requires broad expertise and appropriate software and hardware.A few published works are available which deal with rea
