Electronics

Uncertainty-aware wind and photovoltaic (PV) forecasting must account for grid-related operating constraints. A conditional diffusion framework generates joint 24 h renewable scenarios using separate German EMHIRES series (262,968 hourly values), chronological 70/15/15 partitioning, and a simplified IEEE 14-bus DC benchmark. A cosine noise schedule with a terminal cumulative alpha of 2.43 × 10⁻⁷ was adopted, and DDPM and physics-constrained denoisers were trained using three independent random seeds. Daily persistence, a hybrid wind/PV persistence baseline, a residual-bootstrap baseline, and final-only and reverse-step projection controls were evaluated. For seed 42, PC-Diffusion with physics-gradient guidance achieved an MAE of 0.07401, a CRPS of 0.05153, and 91.80% DC-benchmark feasible trajectories, compared with 0.07404, 0.05289, and 14.61% for DDPM. Hybrid wind/PV persistence achieved a lower MAE (0.06080), while the residual bootstrap obtained a lower CRPS (0.04881). Guided sampling required 22.29 ms per 24 h forecast window, compared with 2.76 ms for DDPM with final-only projection on the evaluated hardware. Raw guided prediction intervals remained undercovered (PICP90 = 71.81%). Validation-calibrated interval bounds achieved 95.25% empirical coverage without changing scenario feasibility, whereas dispersion-based scenario adjustment reduced feasibility. Physics-guided diffusion therefore improves scenario feasibility under training-derived DC constraints, although point-forecast accuracy, probabilistic calibration, and operational feasibility remain subject to important trade-offs.

Optical satellite networks (OSNs) based on low-Earth-orbit (LEO) satellites and optical inter-satellite links (ISLs) are considered a promising component of future high-capacity space communications. However, the high mobility of LEO satellites leads to frequent changes in satellite–ground connectivity, which may cause interruptions in end-to-end optical paths and increase routing instability. To mitigate the impact of frequent satellite–ground handovers, in this paper we investigate routing selection problems for two categories of services with different temporal requirements, namely real-time and time–torrent services. First, a real-time and time–torrent service routing (RTSR) problem was established based on the relevant network and service models. Second, a slow-shot topology model was developed to represent the time-varying network topology through a sequence of snapshots. Third, two routing algorithms, namely slow-shot-based routing selection (SS-RS) and multi-delivery parallel SS-RS (MSS-RS), were proposed to accommodate different service requirements in the time and capacity dimensions, respectively. Extensive simulations were conducted to evaluate the proposed algorithms in terms of their service blocking probability, delivery interruption ratio, bandwidth utilization, and average hop count. The results illustrate the effectiveness of the algorithms, while exhibiting trade-offs regarding service blocking, resource utilization, and routing performance.

This review systematically surveys Sliding-Mode Control (SMC) strategies applied to knee and lower-limb exoskeletons with direct knee-related control or evaluation, emphasising research published over the last decade (2015–2025). The paper first outlines key control challenges arising from nonlinear joint dynamics, external disturbances, sensor feedback, and uncertainties in human–robot interaction. The review then analyses 126 unique studies, including peer-reviewed journal articles and full conference papers, covering classical SMC, higher-order formulations, observer-based architectures, intelligent adaptive schemes, and optimisation-enhanced approaches. Beyond tracking accuracy and chattering behaviour, the review considers practical aspects relevant to wearable rehabilitation systems, including sensing requirements, real-time implementation, patient-specific adaptation, and human–robot interaction. These aspects highlight current methodological trends, practical limitations, and the gap between control performance and real-world rehabilitation use. The review aims to support the development of more robust, safe, and practically deployable control frameworks for knee and lower-limb exoskeletons in rehabilitation applications.