Stratospheric balloons serve as cost-effective platforms for wireless communication. However, these platforms encounter challenges stemming from their underactuation in the horizontal plane. Consequently, controllers must continually identify favorable wind conditions to optimize station-keeping performance while managing energy consumption. This study presents a receding horizon controller based on wind and balloon models. Two neural networks, PredRNN and ResNet, are utilized for short-term wind field forecast. Additionally, an online receding horizon controller, based on simultaneous optimistic optimization (SOO), is developed for action sequence planning and adapted to accommodate various constraints, which is especially suitable due to its gradient-free nature, high efficiency, and effectiveness in black-box function optimization. A reward function is formulated to balance power consumption and station-keeping performance. Simulations conducted across diverse positions and dates demonstrate the superior performance of the proposed method compared with traditional greedy and A* algorithms.

The lift of an aircraft can be effectively enhanced by circulation control (CC) technology at subsonic speeds, but the efficiency at transonic speeds is greatly decreased. The underlying mechanism of this phenomenon is not fully understood. In this study, Reynolds averaged Navier—Stokes simulation with $k-\omega$ shear stress transport model was utilized to investigate the mechanism of lift enhancement by CC in transonic flow. For validation, the numerical CC results were compared with the NASA experimental data obtained for transonic CC airfoil. Thereafter, the RAE2822 airfoil was modified with a Coanda surface. The lift enhancement effects of CC via steady blowing with different momentum coefficients were tested at $Ma=0.3$ and 0.8 at $\alpha =3^{\circ }$, and various fluid mechanics phenomena were investigated. The results indicate that the flow structure of the CC jet is insensitive to the incoming flow conditions because of the similarity to the local static pressure field around the trailing edge of the airfoil. Owing to the appearance of shockwaves on the airfoil surface in the transonic regime, the performance of the CC jet is restricted to the trailing edge of the airfoil. Transonic CC achieved a slight improvement in aerodynamic performance owing to a favorable shift in the shockwave pattern and accelerated flow in the separation region on the airfoil surfaces. Revealing the mechanism of lift enhancement of CC in the transonic regime can facilitate the rational design of new fluidic actuators with high activity and expand the potential applications of CC technology.

Algebraic connectivity and its associated eigenvector, the Fiedler vector, play a fundamental role in maintaining connectivity in multi-agent systems. However, existing estimation methods often suffer from slow convergence. This letter proposes an efficient discrete distributed algorithm, building on prior work, for estimating algebraic connectivity with exponential convergence. And a corresponding method for approximating the Fiedler vector is also developed, making the approach well-suited for connectivity maintenance tasks. Theoretical analysis establishes the convergence conditions for both algorithms. Numerical simulations on weighted and cycle graphs demonstrate that the proposed approach achieves significantly faster convergence compared to original method.