Search Results (2,686)

This paper addresses the consensus problem for networked robotic sensors characterized by general linear dynamics and strict communication bandwidth limitations. We propose a weighted sliding integration-based adaptive dynamic event-triggered control (WSI-ADETC) strategy. First, we design a bounded adaptive parameter using a nonlinear protocol to enhance sensitivity to changes in consensus error. To further alleviate the communication burden on the sensing network, we propose a weighted sliding integration-based event-triggering mechanism to reduce the number of triggers compared to traditional adaptive dynamic event-triggered control (ADETC) approaches. Using Lyapunov analysis, we establish sufficient conditions for asymptotic consensus and demonstrate that the proposed controller effectively eliminates Zeno behavior. Numerical simulations demonstrate that the proposed WSI-ADETC strategy significantly reduces communication frequency while maintaining satisfactory consensus performance. Compared with recent adaptive dynamic event-triggered methods, the proposed method reduces the total triggering number by more than 53%, providing a communication efficient solution for resource-constrained robotic sensing networks. Full article

Medical image analysis is a cornerstone of modern healthcare, yet conventional single-modal deep learning often struggles with the unique physical constraints and structural variability inherent in data acquired from diverse medical sensors. Recently, Vision-Language Models (VLMs) have sparked a paradigm shift by bridging the semantic gap between visual sensor signals and clinical narratives. Following the PRISMA guidelines, 167 representative studies are systematically synthesized in this review to provide a comprehensive roadmap of VLM technological evolution and clinical utility. First, rather than treating VLMs as generic feature extractors, their underlying mechanisms are uniquely distilled into seven core operational principles, which are then explicitly mapped to downstream applications such as few-shot diagnosis, prompt-driven segmentation, and multi-task foundation models. To facilitate intuitive evaluation, a rigorous quantitative cross-comparison of current benchmark architectures is presented. Crucially, this review goes beyond highlighting successes by critically assessing prevalent clinical bottlenecks, including zero-shot segmentation failures, multi-modal hallucinations in diagnosing rare diseases, and the prohibitive computational complexity associated with 3D volumes and gigapixel whole slide images. Finally, a novel, forward-looking framework is proposed: the transition from static “image-text alignment” to dynamic “multi-source sensor-driven intelligence”. By addressing both physical sensor constraints and algorithmic limitations, this survey offers actionable insights for developing trustworthy, sensor-aware clinical diagnostic agents. Full article

The frictional behavior and stability of skid shoe systems are critical to the safety and controllability of walking-type incremental launching for long-span steel truss bridges. Therefore, this study investigates friction control mechanisms and multilayer pad stability through two tests: (1) skid shoe tests to evaluate low-friction performance, sliding stiffness, and the stability of stacked pad assemblies, and (2) interface friction tests to examine the frictional behavior of different material combinations intended to provide high-friction restraint. The results show that Modified Graphene-Enhanced (MGE) plates, when combined with grease and stainless steel, reduce the friction coefficient to 0.017–0.074. High-stack pad assemblies (6–16 layers) exhibited a progressive interlayer slip, with cumulative displacements exceeding the allowable limit, leading to instability; anti-slip measures such as shear keys and segmented restraints were recommended. A load-dependent sliding stiffness relationship, y = 57.46 + 0.00886x, was established to characterize the variation in nominal sliding stiffness with vertical load. The findings provide experimental data and engineering recommendations for the design and operation of skid shoe systems in heavy-load incremental launching applications. The proposed criteria and regression model are applicable to the tested pad geometry, interface configuration, and loading conditions investigated in this study. Full article

This paper introduces an adaptive fixed-time position controller (AFxTPC) designed for the lifting axis servo mechanism of a computer numerical control (CNC) plasma machine. It integrates a permanent magnet synchronous motor, gearbox, and ball screw into a unified electromechanical model. The proposed AFxTPC combines a fixed-time terminal sliding surface function with adaptive fixed-time sliding mode control to achieve fixed-time convergence, precise tracking, and robustness in the presence of parameter uncertainties. A specially designed reaching law guarantees accurate trajectory tracking, while the fixed-time terminal sliding surface function effectively minimizes chattering near the sliding manifold. Importantly, a novel fixed-time nonlinear disturbance observer is developed to simultaneously estimate the unmeasured system states and lumped disturbances in real time within a guaranteed initial-state-independent settling time. These estimated values are explicitly fed back into controller for active disturbance compensation. The stability of the overall closed-loop system is rigorously established using Lyapunov stability theory. Simulation results demonstrate that the proposed observer-based controller achieves superior performance compared with conventional proportional–integral–derivative (PID) and standard sliding mode controllers. It exhibits zero steady-state error, reduced overshoot, minimal chattering, and strong robustness over a wide range of operating conditions. Full article

To enhance drive performance, this paper introduces an advanced speed controller architecture intended for a brushless DC motor (BLDCM) operating under field-oriented control (FOC). This newly developed controller integrates decision tree theory (DTT) with sliding mode theory (SMT). Initially, the regression algorithm from the classification and regression tree (CART) framework is applied to partition the deviation between the actual motor speed and the target command into 10 distinct error zones. These intervals serve as the basis for configuring three critical parameters of a standard exponential reaching law sliding mode controller (ERLSMC): namely, the sliding mode dynamic trajectory control gain, the exponential reaching gain, and the constant speed reaching gain. Following each split, the mean squared error (MSE) of the respective nodes is evaluated to determine the root node. The dataset is recursively bifurcated into dual subsets using the chosen split variables and thresholds, establishing a structured decision pathway through each successive child node. As a result, the sliding mode speed controller receives dynamically optimized modifications for its three key gains in real time during BLDCM operation. In addition, the controller continuously computes an updated sliding mode dynamic trajectory control gain by tracking the derivative of the speed error. Tuning these three operational gains effectively mitigates the transient overshoot typically induced by the conventional exponential reaching law (ERL) across diverse running states. This mechanism ensures that the speed response of the BLDCM drive system dynamically and accurately follows target commands under fluctuating conditions. Advantageously, the introduced control strategy avoids intensive computational routines and eliminates the need for extensive training datasets, ensuring straightforward implementation. To validate this approach, the proposed methodology is applied to the BLDCM drive system using the Matlab/Simulink environment. Its execution is benchmarked against conventional sliding mode controllers (SMCs) configured with three distinct control strategies: the constant speed reaching law (CSRL), the standard ERL, and the extension theory combined with exponential reaching law (ETERL). The resulting simulation data confirms that the proposed adaptive controller delivers superior performance over the alternative three reaching laws regarding both transient command tracking and robustness in load regulation. Full article

The effects of Mn/RE (Nd, Gd) multi-modification on the microstructure and high-temperature compressive creep properties of Mg–8.0Al alloys were investigated. The dominant intermetallic phases in the as-cast microstructure are β-Mg₁₇4Al₁₂, Al₂(Gd,Nd), Al₁₁(Gd,Nd)₃, Al₈(Gd,Nd)Mn₄, and Al₁₀Mn₂(Gd,Nd). The detailed structures of various intermetallics were revealed by TEM; the results indicate that Mn addition promotes grain refinement and facilitates the precipitation of lath-shaped and spherical β-Mg₁₇Al₁₂ in as-cast Mg–Al–RE alloys, resulting in increases in the tensile strength and elongation of the 1.0Mn alloy by 26.5% and 92.1%, respectively. Additionally, thermally stable micron-scale Al₈(Gd,Nd)Mn₄ and Al₁₂(Gd,Nd)₂Mn₅, along with dynamically precipitated spherical nano-sized AlGd and AlNd particles in the α-Mg matrix, were innovatively observed in compression-crept specimens tested at 200 °C and 60 MPa; these phases play a key role in improving high-temperature creep resistance. A significant finding is that excessive Mn addition deteriorates creep performance, which is attributed to excessive grain refinement and the consequent increase in the contribution of grain boundary sliding during creep. However, the negative effect of grain boundary sliding—caused by grain refinement—on creep performance can be balanced by the strengthening effect of Al–Mn–Gd phases and the dynamic precipitation of nanoscale Al–RE particles. This paper provides new insights for designing Mg–Al–Nd–Gd–Mn alloys with both excellent high-temperature creep resistance and significantly enhanced mechanical properties. Full article

With the construction of transportation networks in mountainous areas under the Western Development Strategy, double-row pile foundations on slopes have been widely applied. However, due to the distortion of the soil stress field, their load distribution mechanism under bidirectional loading is extremely complex. To investigate the internal force distribution laws and deformation and failure modes, a systematic study was conducted utilizing theoretical derivation: 60 scale indoor physical model tests, and 3D refined finite element numerical simulations. The results show that the force distribution of double-row piles in slope environments differs significantly: the upper-row piles, affected by active earth pressure and sliding thrust, bear significantly higher load than the lower-row piles; meanwhile, the lower-row piles, constrained by stronger deep soil, can more fully utilize their vertical bearing capacity. Parametric analysis indicates that the terrain slope has a nonlinear amplification effect on the displacement difference at the pile top, with 50° being the critical mutation slope that triggers the failure of connection joints. In addition, the deformation mode of double-row piles undergoes a change when the pile spacing exceeds 5 times the pile diameter. Therefore, in practical engineering design, the traditional concept of symmetrical reinforcement should be abandoned in favor of differentiated bending reinforcement targeting the shallow surface layer of the upper-row piles and the deep inflection point of the lower-row piles. For working conditions with a slope greater than 50°, additional measures such as prestressed anchor cables must be applied to reduce the sliding load. Meanwhile, the row spacing should be strictly controlled within 5 times the pile diameter to fully ensure the diaphragm effect and the overall synergistic stability of the structure. Full article

Rainstorm-induced disaster chains are characterized by high suddenness, immense destructive power, and complex chain propagation mechanisms. Traditional static assessment methods rely on fixed parameters and struggle to depict the dynamic evolution of such disasters. Existing dynamic models are mostly based on predefined structures and lack the capability to integrate multi-source data and quantify uncertainty, thereby constraining the accurate prediction of rainstorm disaster chains. To address these issues, this study proposes a rainstorm disaster chain prediction model (SW-DBN) that integrates a large language model (LLM)-optimized sliding window mechanism with a dynamic Bayesian network (DBN). The model first performs dynamic segmentation and feature extraction on multi-source time-series data through the sliding window mechanism and constructs an LLM-driven module for semantic understanding of multi-source information and latent parameter mining. By leveraging the LLM’s in-depth analysis of data pattern variations within the window, the model excavates latent parameters, adaptively adjusts the DBN network topology, and feeds back to optimize the window width and sliding step, thereby maintaining adaptive alignment between the sliding window’s feature extraction and the dynamic evolution of the disaster chain. Ultimately, the cascade propagation process of the rainstorm disaster chain is modeled, reasoned, and validated through the DBN, forming an integrated prediction framework of “perception–reasoning, dynamic regulation, and cascade verification.” A case study in the Xi’an area demonstrates that the proposed model can effectively simulate the temporal evolution of rainstorm disaster chains. The average prediction accuracy for four key types of disaster nodes reaches 84.8%, representing an improvement of 7.5 percentage points over the standard DBN model, with clear advantages in early warning timeliness for critical nodes. The proposed model provides technical support for the probabilistic prediction of rainstorm disaster chains and disaster prevention decision-making, featuring both dynamic adaptability and interpretability. Full article

Conventional transient stability assessment in multi-machine power systems relies predominantly on fixed thresholds, which exhibit limited adaptability to varying operating conditions and fail to provide a unified analytical framework for rotor angle and voltage stability. To address these challenges, this paper proposes an adaptive threshold warning method based on geometric algebra. A multi-dimensional unified state vector incorporating generator rotor angles, speeds, electromagnetic powers and bus voltage magnitudes and phases is constructed to map system dynamics onto a high-dimensional geometric trajectory. The second- and third-order wedge products of this trajectory are computed to quantify disturbance severity and volumetric expansion preceding instability. An adaptive threshold mechanism is established utilizing sliding window robust statistics (Median Absolute Deviation) to track the trajectory’s instantaneous dimension in real time. Validation on the IEEE 39-bus system demonstrates that the proposed method issues a warning at t = 4.90 s, achieving a detection advance of 0.30 s relative to the conventional 30° rotor angle separation threshold. The method exhibits strong noise robustness with only 40 ms warning delay under 20 dB SNR conditions, and effectively captures rotor angle–voltage coupling characteristics. The geometric algebra framework offers a unified assessment tool with distinct advantages in computational speed, adaptivity, and interpretability. Full article

This study presents a computational and experimental aerodynamic characterisation of a full-scale 5.5 m diameter, six-sail horizontal-axis windmill of the traditional Cretan Lasithi type, equipped with flexible woven polyester sails that act as a passive load-control mechanism. Seventeen operating points spanning wind speeds of 2.3–18.3 m/s were simulated in OpenFOAM using a transient sliding-mesh Arbitrary Mesh Interface formulation with the k–ω SST turbulence closure on a 2.3 million cell grid, selected on the basis of a four-level grid convergence study. CFD simulations identify three distinct aerodynamic regimes: a drag-dominated high-TSR regime (λ > 2.1), a mixed lift–drag working range with peak loading near λ ≈ 1.4–1.5, and a deep-stall regime in which boundary-layer separation propagates from root to tip as λ falls below 1.0. Field measurements conducted at the Energy Systems Synthesis Lab of the Hellenic Mediterranean University in compliance with IEC 61400-12-1:2005(E) confirm that rotor speed stabilises passively at 55–58 RPM above 13 m/s without any active control mechanism; CFD predictions agree with measured power output within 8–12% across the 2–13 m/s attached-flow envelope. The combined evidence indicates that passive overspeed self-regulation is driven by aeroelastic sail deformation, reducing effective disc solidity at high wind speeds, a mechanism that rigid-geometry CFD correctly identifies in trend but cannot quantify in magnitude. The primary limitation of the present work is the rigid-sail assumption of the CFD model, which requires a two-way coupled fluid–structure interaction extension as a future step. Full article

Copper and its alloys are widely used in electrical, automotive, aerospace, and energy applications because of their excellent thermal and electrical conductivity. However, the low hardness and poor wear resistance of pure Cu limit its use under tribologically demanding sliding conditions. In this study, Cu matrix composites reinforced with 1 wt.% boron carbide (B₄C), boron (B), chromium (Cr), cobalt (Co), alumina (Al₂O₃), and graphite (Gr) were fabricated by powder metallurgy and comparatively evaluated under identical processing and testing conditions. Phase constitution and microstructural characteristics were analyzed by XRD, SEM, and EDS, while mechanical and tribological behavior was assessed by Vickers hardness and dry sliding wear tests. All reinforcements improved the hardness of the Cu matrix compared with unreinforced Cu. The hardness increase followed the order Cu–B₄C (68.91%) > Cu–B (66.43%) > Cu–Gr (63.97%) > Cu–Al₂O₃ (61.79%) > Cu–Cr (42.69%) > Cu–Co (36.04%). Dry sliding wear tests, performed under a 10 N normal load, 0.05 m s⁻¹ sliding speed, and 1000 m sliding distance against a 316L stainless-steel ball, showed that all reinforced composites exhibited lower mass loss and more stable sliding behavior than pure Cu. Among all samples, Cu–B₄C displayed the best wear performance, with a 154.8% improvement in wear resistance relative to pure Cu. SEM analysis of the worn surfaces revealed that reinforcement addition reduced severe plastic deformation, groove formation, and delamination, leading to a more stable wear regime. Graphite- and boron-containing composites benefited from interfacial lubrication and contact stabilization, whereas B₄C and Al₂O₃ improved wear resistance through rigid-particle strengthening and enhanced load-bearing capacity. By comparing ceramic, metalloid, metallic, oxide, and solid-lubricating reinforcements at the same low addition level and under identical processing and testing conditions, this study provides a reinforcement-selection framework for Cu-based composites requiring improved hardness and dry-sliding durability. Full article

The temperature-dependent wear behavior of a cobalt-based Stellite 6 alloy was investigated from room temperature (RT) to 800 °C using high-temperature reciprocating sliding tests. The friction coefficient decreases monotonically with increasing temperature, from about 0.56 ± 0.12 at RT to 0.26 ± 0.11 at 800 °C, whereas the wear rate exhibits a pronounced non-monotonic evolution. Specifically, the wear rate increases from 18.4 ± 1.5 × 10⁻⁶ mm³·N⁻¹·m⁻¹ at RT to a maximum of 54.8 ± 1.6 × 10⁻⁶ mm³·N⁻¹·m⁻¹ at 600 °C, followed by an anomalous reduction to 10.2 ± 1.5 × 10⁻⁶ mm³·N⁻¹·m⁻¹ at 800 °C, which is even lower than that at RT. Microstructural and elemental analyses indicate that this behavior is governed by the temperature-dependent evolution of oxide layers. At RT–600 °C, thin and mechanically unstable oxide films repeatedly form and fracture, promoting oxidation-assisted abrasive and adhesive wear. In contrast, at 800 °C, a continuous and dense oxide layer forms and acts as a stable tribo-oxide film, effectively suppressing severe material removal. These findings clarify the temperature-driven wear mechanism transition of Stellite 6 alloy under high-temperature sliding conditions. Full article

Autonomous navigation of a vehicle in an environment where there are obstacles is difficult due to low onboard sensing technology, high measuring noise, and external interference, which collectively result in poor tracking performance of the vehicle’s trajectory and compromise safety. In this paper, a UAV-assisted Distributed Sliding Mode Control (DSMC) is proposed to robustly and safely implement path tracking for autonomous ground vehicles (AGVs). The proposed system utilizes an aero-sensor layer for enhanced perception, such as obstacle sensing, reference path preview, and look-ahead trajectory information, and it shares this information with the vehicle via wireless communication. The fundamental scheme, called DSMC, is based on a conventional Sliding Mode Control (SMC) technique and uses UAV preview-based feedback. This allows anticipation of control actions to enhance tracking performance and achieve more timely, smoother obstacle avoidance than baseline SMC. The proposed method is designed to overcome the limitations of traditional SMC strategies, such as chattering and poor responsiveness. The proposed method features continuous nonlinear approximation and damping mechanisms to reduce chattering and improve response characteristics, thereby enhancing stability and reducing oscillations. Strict safety enforcement through constraint is always achieved by keeping the vehicle and obstacles separated by a minimum distance only; that is, a minimum distance is always guaranteed: a Constraint Barrier Function (CBF)-based constraint is used. By combining UAV-assisted perception with DSMC and CBF the system can guarantee its formal safety in the presence of disturbances and sensing uncertainties while maintaining accurate trajectory tracking. Based on our simulation results, the proposed UAV-assisted DSMC method is shown to be significantly superior to conventional SMC and Model Predictive Controller (MPC) in terms of tracking accuracy, control smoothness, and adherence to the safety margin. Our simulation results demonstrate that the proposed method significantly outperforms conventional SMC and MPC control. Specifically, it achieves a 22.9% reduction in RMSE (0.135 m vs. 0.175 m) and 63% lower mean control effort, and it strictly maintains the minimum safety distance under both static and dynamic obstacles. The algorithm runs in real-time with an average execution time of 1.85 ms (>200 Hz), making it highly suitable for embedded deployment. These results highlight the effectiveness of combining UAV-assisted preview, adaptive robust control, and formal safety constraints for reliable autonomous navigation in complex environments. Full article

The increasing demand for sustainable and lightweight furniture systems has driven interest in additively manufactured polymer components as alternatives to conventional metal hardware. However, their performance at the functional assembly level under standardized loading conditions remains insufficiently explored. This study evaluates the feasibility of replacing metal drawer slides with fused deposition modeling (FDM)-based polymer alternatives fabricated from polylactic acid (PLA) and polyethylene terephthalate glycol (PETG). Unlike previous studies focused on material-level characterization, this work investigates fully functional drawer slide assemblies integrated into medium-density fiberboard (MDF) systems, enabling component-level assessment under realistic conditions. Specimens were designed in SolidWorks and fabricated under controlled printing parameters. Commercial metal slides were used as benchmarks. Mechanical performance was tested according to BS EN standards, and deformation was measured at multiple points. Statistical analysis included ANOVA, Tukey HSD, and t-tests at a 95% confidence level. Results showed significant differences among materials (p < 0.05). Metal slides exhibited the highest stiffness and minimal deformation. PLA showed stable performance with minor surface degradation, while PETG demonstrated lower dimensional stability and premature failure due to higher compliance. Overall, PLA-based FDM components offer a cost-effective alternative for non-heavy-duty applications, whereas PETG requires further optimization. The study bridges additive manufacturing and real-world furniture component performance under standardized testing. Full article

To address the bottlenecks of conventional valve-controlled marine steering systems—characterized by high throttling losses, low efficiency, and high leakage risk—as well as the insufficient power density and impact resistance of electro-mechanical actuators (EMAs) for high-load steering of large vessels, this paper proposes and validates a high-performance integrated solution for an electro-hydrostatic actuator (EHA) for ship steering. First, a fifth-order electro–hydraulic–mechanical coupled dynamic model comprising a permanent magnet synchronous motor, hydraulic pump, hydraulic cylinder, and load is established. The validity and applicability boundaries of three simplifying assumptions—neglecting leakage, pipeline pressure losses, and steady-state fluid compressibility effects—are quantitatively analysed, with a total introduced error ≤3%. These assumptions are justified under medium-pressure, short-pipeline, and well-sealed conditions typical of marine EHA systems. Second, a composite control architecture combining outer-loop sliding mode control with inner-loop motor PID dual-loop control is proposed. Parameter tuning is performed using pole placement for the sliding surface and the Ziegler–Nichols critical ratio method for the inner loops, effectively suppressing hydraulic system parameter perturbations and random wave-induced load disturbances. Quantitative comparisons show that the proposed method reduces overshoot by 11.63% and improves sinusoidal tracking accuracy by 90.13% compared to conventional single-loop PID control. An integrated drive-control structure is designed, and a three-phase full-bridge inverter main circuit with wide-voltage input capability—including EMI filtering, soft-start, and LC filtering—is developed to accommodate the ±20% voltage fluctuations typical of ship power grids, thereby enhancing system integration and grid adaptability. Phased bench tests demonstrate that the settling time from no-load start-up to 200 r/min is only 0.01 s. When a sudden 20 N·m load is applied, the speed drop is less than 3%, and the recovery time is less than 0.025 s. The steady-state steering angle error does not exceed 0.12°, the maximum average steering rate reaches 3.33°/s, and the steering response time is within 0.3 s. All core performance indicators exceed the general technical standards for marine steering systems, with a 65.7% improvement in steady-state accuracy and a 62.5% improvement in response speed over conventional PID control. The research findings provide an effective general technical solution and experimental data support for the performance optimization and engineering application of marine EHA systems. Full article