Autonomic optimized path planning method for solar-powered aircraft

A technology for solar-powered aircraft and track planning, applied in three-dimensional position/course control, non-electric variable control, instruments, etc., can solve problems such as heavy dependence on solar irradiance, low flight speed, and affecting the working status of solar-powered drones

Active Publication Date: 2018-06-01
BEIHANG UNIV
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Problems solved by technology

Solar-powered UAVs are also facing many severe challenges, such as the sensitivity to environmental conditions caused by the lightweight design of the structure,

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  • Autonomic optimized path planning method for solar-powered aircraft
  • Autonomic optimized path planning method for solar-powered aircraft
  • Autonomic optimized path planning method for solar-powered aircraft

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Embodiment Construction

[0031] According to the solar-powered aircraft autonomous optimization track planning method of the present invention, the system model of the UAV is closely combined with the meteorological conditions, and the design goal is to use the random forest algorithm to plan the flight path of the aircraft according to the meteorological data under partly cloudy conditions , so as to realize the multi-day flight of the aircraft, ensure the flight safety of the aircraft and complete the tasks specified by the user as required.

[0032] The system model and algorithm based on the solar-powered aircraft autonomous optimization trajectory planning method according to the present invention include meteorological forecast data, system power and energy model, objective function (cost function) and initial conditions, departure / arrival position and discrete grid, Random forest algorithm, path optimization results (planning path information). The system model takes into account the flight dyn...

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Abstract

The invention relates to a random forest algorithm-based path optimization method for a long-endurance solar aircraft. The method is mainly applied to the path planning of a long-endurance solar-powered aircraft in response to climate environments. The method is mainly composed of the following components: meteorological forecast data, a system dynamic and energy model, an objective function (costfunction), initial conditions, a departure/arrival position, a discrete grid, a random forest algorithm, and a path optimization result (planning path information). According to the method, the comprehensive objective function is established, the influence of many factors on the flight safety of the aircraft is considered; historical data can be flexibly analyzed, so that a flight mission can beplanned in advance; and online flight path correction can be performed quickly and efficiently. The method is not limited to the path planning of the solar-powered aircraft in response to the climaticenvironments; and with the objective function modified, the method can be extended to flight path planning in environments such as high mountain areas.

Description

technical field [0001] The invention relates to a method for autonomously optimizing flight path planning of a solar-powered aircraft. Background technique [0002] The long-endurance solar aircraft is an unmanned aerial vehicle that uses solar energy as the main energy supply system and can fly continuously at low and high altitudes for more than several weeks. Because it can complete most of the work of satellite reconnaissance, early warning, atmospheric observation, and relay communication, the long-endurance solar-powered aircraft is currently receiving the attention of various aerospace powers. Today's solar-powered unmanned aerial vehicle, combined with a highly optimized aerodynamic shape and a high-efficiency solar charging system, has continuously improved its ability to fly for a long time. For example, the "Sky Envoy" and "Zhefeng" UAVs have achieved multi-day or "nominal" permanent flight. The aforementioned two can respectively represent the two development t...

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Application Information

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IPC IPC(8): G05D1/10
CPCG05D1/101
Inventor 李可文东升胡庆雷刘猛孙康文
Owner BEIHANG UNIV
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