Remaining useful life (RUL) prediction is a core task in prognostics and health management. While Transformers excel at modeling long-range temporal dependencies, their performance is highly sensitive to hyperparameters, and improper splitting of sliding-window samples can introduce data leakage. We propose a Sparrow Search Algorithm (SSA)-optimized Transformer for CMAPSS RUL prediction, adopting an engine-wise split for leakage-aware model selection and using validation RMSE as the fitness function to guide SSA-based hyperparameter optimization. On the FD001 test set, the model achieves RMSE $13.79$, MAE $10.00$, $R^2=0.88$, and a NASA score of $356.26$. The prediction curves and residual d... More >

The operational reliability of aeroengines is vital to civil aviation safety; however, bearings and other key components are prone to failure under harsh operating conditions. In real-world monitoring data, severe class imbalance often leads conventional fault diagnosis methods to be biased toward majority classes, limiting their ability to identify critical faults. To address this issue, this paper proposes a robust anomaly detection framework that integrates the Synthetic Minority Oversampling Technique (SMOTE) with a Broad Learning System (BLS). SMOTE is first applied to generate synthetic fault samples in the feature space, thereby balancing the data distribution and reducing bias. The b... More >

This paper develops a general and implementation friendly stability framework for self-learning control (SLC) laws of the form $u(t)=k_1(t)u(t-\tau)+k_2 v(t)$. Uniform ultimate boundedness is established for a class of general linear plants under two engineering actuator assumptions: (i) smoothness and (ii) saturation with maximum value. These assumptions are reasonable for practical systems and yield an explicit bound, which converts the delay learning mechanism into a nominal (delay-free) controller plus a bounded perturbation injection. The most notable feature of SLC is its simplicity of structure coupled with excellent performance. It is compatible with traditional algorithms and can e... More >

This study investigates the finite-time attitude tracking problem of spacecraft. We employ finite-time control methods to develop a novel adaptive controller. The controller utilizes a time-varying non-singular adaptive fast terminal sliding mode. The time-varying sliding mode dynamically adjusts the sliding surface morphology. This adjustment enables precise control performance tuning. Additionally, adaptive methods estimate the upper bound of generalized disturbances. This estimation reduces the computational load of the controller. The proposed controller demonstrates high robustness against external disturbances and inertia uncertainties. Lyapunov methods prove the stability of the contr... More >

Fixed-wing unmanned aerial vehicle (UAV) formation technology, as a crucial research direction in multi-agent system cooperative control, while facing constraints in multiple areas, has demonstrated broad application prospects in military reconnaissance, disaster monitoring, agricultural plant protection and other fields in recent years. This paper systematically reviews the key technological systems of fixed-wing UAV formation control, including formation configuration design, communication topology, cooperative control algorithms, navigation positioning and obstacle avoidance strategies. By analyzing the latest research progress, the performance differences between centralized and distribu... More >

Inaugural Editorial: A welcome message from the Editor-in-Chief of Aerospace Engineering Communications. More >