Abstract
In order to reduce the cost of the flight controller and improve the control accuracy of solar-powered unmanned aerial vehicle (UAV), three state estimation algorithms based on the extended Kalman filter (EKF) with different structures are proposed: Three-stage series, full-state direct and indirect state estimation algorithms. A small hand-launched solar-powered UAV without ailerons is used as the object with which to compare the algorithm structure, estimation accuracy, and platform requirements and application. The three-stage estimation algorithm has a position accuracy of 6 m and is suitable for low-cost small, low control precision UAVs. The precision of full-state direct algorithm is 3.4 m, which is suitable for platforms with low-cost and high-trajectory tracking accuracy. The precision of the full-state indirect method is similar to the direct, but it is more stable for state switching, overall parameters estimation, and can be applied to large platforms. A full-scaled electric hand-launched UAV loaded with the three-stage series algorithm was used for the field test. Results verified the feasibility of the estimation algorithm and it obtained a position estimation accuracy of 23 m.
Highlights
Solar-electrically powered fixed-wing unmanned aerial vehicles (UAVs) promise significantly increased flight endurance over pure electrically or even gas-powered aerial vehicles.Large-scale disaster relief, meteorological surveys in remote areas, and continuous border or wildlife protection benefit in particular from the multi-hour continuous flight capability provided by these robotic systems [1]
A full-scale electronic UAV, with a wingspan of 3 m and a weight of 3 kg without solar cells, A full‐scale electronic UAV, with a wingspan of 3 m and a weight of 3 kg without solar cells, was equipped with a low-cost flight controller and the three-stage series estimation algorithm were was equipped with a low‐cost flight controller and the three‐stage series estimation algorithm were loaded for the full mission flight verification (Figure 14)
This paper begins with the cost of the flight controller of a hand-launched solar-powered UAV
Summary
Solar-electrically powered fixed-wing unmanned aerial vehicles (UAVs) promise significantly increased flight endurance over pure electrically or even gas-powered aerial vehicles. The flight controller consisting of a low-cost micro-electro-mechanical system (MEMS), inertial measurement unit (IMU), magnetometer, GPS and barometer has a great price advantage, but it lacks measurement accuracy and long-time reliability, and cannot be directly applied to a solar-powered UAV platform [7]. By using the appropriate state estimation algorithm, the measurement accuracy of the low-cost sensor is effectively improved to meet the trajectory tracking accuracy requirements [9], for example, a four-sided route with an area of 1 km has an acceptable tracking error of approximately 30 m (30 m/km2 ), and a heading error of nearly 13 degrees, thereby reducing the cost of the flight controller. Three novel state estimation algorithms are proposed to improve the measurement accuracy of, low-cost sensors, reduce the cost of flight controller, and realize the application of three-stage.
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