Fallible Humans and Vulnerable Systems: Lessons Learned from Aviation
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Autopilot
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Abstract The objective of this chapter is to give an overview of autopilot software design for small and miniature unmanned air systems. An architecture that is typical of commercially available autopilots is described. A detailed explanation of the inner‐loop control structure is described, including the lateral directional feedback loops and the longitudinal directional feedback loops. We give a brief description of the sensor package that is usually on small UAS, and describe simple filtering schemes for extracting estimates of the states needed by the autopilot. Finally, we briefly describe GPS navigation for following straight lines and orbits.
Autopilot
Feedback loop
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This paper presents a survey of the autopilot systems for small fixed-wing unmanned air vehicles (UAVs). The UAV flight control basics are introduced first. The radio control system and autopilot control system are then explained from both hardware and software viewpoints. Several typical commercial off-the-shelf autopilot packages are compared in detail. In addition, some research autopilot systems are introduced. Finally, conclusions are made with a summary of the current autopilot market and a remark on the future development.This paper presents a survey of the autopilot systems for small fixed-wing unmanned air vehicles (UAVs). The UAV flight control basics are introduced first. The radio control system and autopilot control system are then explained from both hardware and software viewpoints. Several typical commercial off-the-shelf autopilot packages are compared in detail. In addition, some research autopilot systems are introduced. Finally, conclusions are made with a summary of the current autopilot market and a remark on the future development.
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Fixed wing
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Research on course-keeping control,track-keeping control and other functions of ship autopilot at home and abroad is introduced in the paper.Combining the ship autopilot research with the e-Navigation project of IMO,development trend of ship autopilot research is presented in the aspects of advanced algorithm,functional integration,network-based system,convenience in utilization,and localization of equipments.
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The control methods of ship maneuvering autopilot were described and compared. The ship autopilots contain four developmental stages, t hat is, mechanical, PID, adaptive and intelligent control autopilot. The intelli gent autopilot is now the most advanced autopilot, its control methods can be di vided into expert system, fuzzy control and neural network.
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Autopilot
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Abstract Aviation emissions are the fastest growing source of anthropogenic greenhouse gas emissions. Aviation emissions from Annex I Countries increased by 67% between 1990 and 2005 and, according to some estimates, by as much as 90% when aviation emissions from non-Annex I Countries are included for this period. This chapter examines the current status of international aviation under the United Nations Framework Convention on Climate Change (UNFCCC), the ongoing debate over developing measures under the International Civil Aviation Organization (ICAO) or including the sector in a post-2012 agreement, the moves by the EU to bring international aviation under the European Union Emission Trading Scheme (EU ETS), and issues that will need to be considered when implementing measures at the international level to reduce the sector's emissions.
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This paper develops an adaptive digital autopilot for quadcopters and presents experimental results. The adaptive digital autopilot is constructed by augmenting the PX4 autopilot control system architecture with adaptive digital control laws based on retrospective cost adaptive control (RCAC). In order to investigate the performance of the adaptive digital autopilot, the default gains of the fixed-gain autopilot are scaled by a small factor, which severely degrades its performance. This scenario thus provides a venue for determining the ability of the adaptive digital autopilot to compensate for the detuned fixed-gain autopilot. The adaptive digital autopilot is tested in simulation and physical flight tests, and the resulting performance improvements are examined.
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Digital Control
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The dynamic characteristics of acceleration autopilot and attitude autopilot are discussed in detail. Also, a comparison study was made between these two different types of control schemes for guidance loop. By means of simulation, it is concluded that the guidance accuracy is mainly determined by the slowest subsystem among different system dynamics. For air-to-ground missiles, with limited terminal guidance time, the control scheme of acceleration autopilot combined with proportional navigation guidance (PNG) law is the better choice.
Autopilot
Proportional navigation
Missile Guidance
Terminal guidance
Guidance system
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This paper develops an adaptive digital autopilot for quadcopters and presents experimental results. The adaptive digital autopilot is constructed by augmenting the PX4 autopilot control system architecture with adaptive digital control laws based on retrospective cost adaptive control (RCAC). In order to investigate the performance of the adaptive digital autopilot, the default gains of the fixed-gain autopilot are scaled by a small factor, which severely degrades its performance. This scenario thus provides a venue for determining the ability of the adaptive digital autopilot to compensate for the detuned fixed-gain autopilot. The adaptive digital autopilot is tested in simulation and physical flight tests, and the resulting performance improvements are examined.
Autopilot
Digital Control
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The attitude autopilot and the velocity orientation autopilot of the flying vehicle swerve phase are designed and compared in this paper. The analysis result shows that the response speed of the velocity orientation autopilot is far faster than the attitude autopilot by reasonably designing, and the stability of the velocity orientation autopilot is better than the attitude autopilot.
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