Xiaojun Zhang

During the suspension flight of high-altitude scientific balloons in near-space, they are highly vulnerable to time-varying wind field disturbances, which tend to excite multiple distinctive torsional modes of the balloons themselves, thereby interfering with the observations of balloon-borne equipment. Focusing on the azimuth control of the balloon-borne gondola, this paper designs a simplified decoupling mechanism and a reaction wheel as actuators. Specifically, the reaction wheel achieves azimuth tracking through angular momentum exchange, while the simplified decoupling mechanism performs the functions of decoupling and unloading. To fully utilize the control performance of the actuating structure, this paper further proposes a control algorithm based on a nonlinear differential tracker and neural network PID. Simulation results demonstrate that under typical wind disturbances and sensor noise conditions, the proposed system exhibits excellent smoothness and high-precision and stable control performance. This research provides a significant basis for stable observation platforms in precise near-space observation missions.

Current stratospheric airships generally employ photovoltaic cycle energy systems. Accurately calculating their power generation is significant for airships’ overall design and mission planning. However, the power generation of solar arrays on stratospheric airships is challenging to model and calculate due to the dynamic nature of the airships’ flight, resulting in continuously changing radiation conditions on the curved surface of the airships. The power generated by the airship solar array was modeled herein through a combination of the flight attitude, spatial position, time, and other influencing factors. Additionally, the model was modified by considering the variation in photovoltaic conversion efficiency based on the radiation incidence angle, as well as the state of charge and power consumption of the energy storage battery pack. This study compared the measurement data of power generation in real flight tests with the calculation results of the model. The comparison showed that the results of the calculated model were highly consistent with the actual measured data. An average normalized root-mean-square error of 2.47% validated the accuracy of the newly built model. The generalizability and rapidity of the model were also tested, and the results showed that the model performed well in both metrics.