This article researches the improvement of dynamics stability of the ducted fan unmanned aerial vehicles by optimizing its mechanical–structure parameters. The instability phenomenon of ducted fan unmanned aerial vehicles takes place frequently due to the complicated airflow in near-earth space, which easily leads to the stability problems, such as out of control, shaking, and loss accuracy of command tracking. The dynamics equations mirror its dynamics characteristics, which are primarily influenced by the mechanical–structure parameters of the whole system. Based on this, the optimization of mechanical–structure parameters has a significant to improve the dynamics stability of the whole system. Therefore, this article uses the concept of Lyapunov exponents to build the quantification relationship between system’s mechanical–structure parameters and its motion stability to enhance its stability from viewpoint of mechanical–structural parameter design. The takeoff, landing, and hovering stage are respectively studied and the conclusions suggest that the optimization of mechanical–structure parameters can be used to promote dynamics stability.
This paper proposes an improved 3D-Vector Field Histogram (3D-VFH) algorithm for autonomous flight and local obstacle avoidance of multi-rotor unmanned aerial vehicles (UAVs) in a confined environment. Firstly, the method employs a target point coordinate system based on polar coordinates to convert the point cloud data, considering that long-range point cloud information has no effect on local obstacle avoidance by UAVs. This enables UAVs to effectively utilize obstacle information for obstacle avoidance and improves the real-time performance of the algorithm. Secondly, a sliding window algorithm is used to estimate the optimal flight path of the UAV and implement obstacle avoidance control, thereby maintaining the attitude stability of the UAV during obstacle avoidance flight. Finally, experimental analysis is conducted, and the results show that the UAV has good attitude stability during obstacle avoidance flight, can autonomously follow the expected trajectory, and can avoid dynamic obstacles, achieving precise obstacle avoidance.
Among current detection methods of the atmospheric boundary layer, sounding balloon has disadvantages such as low recovery and low reuse rate, anemometer tower has disadvantages such as fixed location and high cost, and remote sensing detection has disadvantages such as low data accuracy. In this paper, a meteorological element sensor was carried on a six-rotor UAV platform to achieve detection of meteorological elements of the atmospheric boundary layer, and the influence of different installation positions of the meteorological element sensor on the detection accuracy of the meteorological element sensor was analyzed through many experiments. Firstly, a six-rotor UAV platform was built through mechanical structure design and control system design. Secondly, data such as temperature, relative humidity, pressure, elevation, and latitude and longitude were collected by designing a meteorological element detection system. Thirdly, data management of the collected data was conducted, including local storage and real-time display on ground host computer. Finally, combined with the comprehensive analysis of the data of automatic weather station, the validity of the data was verified. This six-rotor UAV platform carrying a meteorological element sensor can effectively realize the direct measurement of the atmospheric boundary layer and in some cases can make up for the deficiency of sounding balloon, anemometer tower, and remote sensing detection.
This paper addresses the issue of dynamic instability in quadrotor caused by changes in load mass during flight. To tackle this problem, the Lyapunov exponent method is adopted to study the dynamics and motion stability of the system. This approach resolves the challenge of constructing system eigenvalues due to the nonlinearity and high order of the quadrotor. To enhance the reliability of stability analysis, a quantitative relationship between system dynamics parameters and motion stability is established by combining the dynamic model with the Lyapunov exponent method. This approach compensates for inaccuracies in theoretical modeling analysis caused by factors such as load mass changes. The experiments demonstrate that changing the wheelbase and load mass improves flight motion stability, ensuring the reliability of the quadrotor flight system. Overall, this paper provides an in-depth analysis of the motion stability of a quadrotor and proposes a reliable method for stability analysis that accounts for changes in load mass during flight.
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