Search Results (323)

Examining the mechanism of two-way interaction between the air turbine and generator is essential for accurately predicting the performance of oscillating water column (OWC) devices. This study developed a fully integrated model for a back-bent duct buoy device, which incorporated the chamber, impulse turbine, permanent magnet synchronous generator, PI controller, and speed control strategies. The models of chamber–turbine and turbine-control systems were validated separately against wave-flume experimental results under regular and irregular wave conditions. In addition, a comparative study of two control strategies based on Best Efficiency Point Tracking was conducted by analysing key performance parameters at each energy conversion. The mechanism of two-way interaction between the turbine and the generator was elucidated. The integrated model demonstrated a great potential in predicting the conversion performance of wave energy to electrical energy under real sea conditions, as well as testing control strategies and algorithms before physical deployment. Full article

The irregular geometry of highway tunnel linings, combined with uneven terrain and external disturbances, often causes inspection robots to deviate from their predefined paths. Due to the strong coupling inherent in robotic systems, these deviations propagate to the end-effector, significantly compromising automated inspection accuracy and effectiveness. To tackle these issues, this study introduces an Enhanced Extended Sliding Mode Predictive Control (EESMPC) method, which integrates an adaptive Extended State Observer (ESO). The algorithm is derived from the robot chassis model and a desired trajectory error model, enabling precise contour profile tracking. Crucially, the integrated ESO actively estimates and compensates for unmodeled disturbances and system uncertainties within the state feedback, thereby enhancing both path tracking stability and precision. Comparative MATLAB simulations and experimental path tracking tests evaluated the performance against three other controllers. The results demonstrate that the EESMPC algorithm achieves superior tunnel lining tracking performance, exhibiting marked improvements in both tracking accuracy and system robustness. Consequently, this approach significantly enhances the automated inspection accuracy and operational efficiency of highway tunnel inspection robots. Full article

This study evaluates the tracking performance of structural damages in disaster environments by combining YOLOv8 detection with the BoT-SORT tracker. Cracks and exposed rebar, characterized by fine and irregular structures, showed high sensitivity to viewpoint changes, with camera motion compensation (CMC) improving $IoU$ by +19.63% and +20.23%. For exposed rebar, the joint use of CMC and re-identification (Re-ID) further increased $IDF1$ by +37.73%, emphasizing the effectiveness of appearance-based matching. In contrast, delamination and concrete debris, with stable morphology and clear boundaries, exhibited limited benefits from CMC, improving $IoU$ by +11.17% and +3.28%. Analysis of $MOTA$, $IDF1$, and $HOTA$ confirms that fine-grained damages require motion- and appearance-based strategies, while stable types maintain high performance through detection consistency. These results highlight the importance of tailored tracking strategies for enhancing disaster-response robots and structural monitoring systems. Full article

The rehabilitation training of patients with lower limb motor dysfunction highly relies on the precise control of biomimetic knee joint robots. Existing control strategies generally suffer from insufficient control accuracy and weak anti-interference ability, and an optimization plan that balances high precision and strong anti-interference has not yet been formed, which seriously affects the effectiveness of rehabilitation training. In order to improve the control accuracy and anti-interference ability of biomimetic knee joint robots for leg rehabilitation training of patients with lower limb movement disorders, the purpose of this study is to address the performance shortcomings of existing biomimetic knee joint robot control strategies. The goal is to propose a high-precision and strong anti-interference control strategy to provide more reliable rehabilitation support for patients with lower limb movement disorders. Therefore, this article proposes an optimization strategy based on the Spider Bee Algorithm (SWO) combined with fuzzy PID control. Based on a biomimetic knee joint robot model, this study simulates three common pathological states of knee joint ligament injury, meniscus injury, and muscle atrophy in patients, and compares the trajectory tracking and anti-interference performance of PID, fuzzy PID, and SWO fuzzy PID control strategies. The experimental results show that the SWO fuzzy PID control strategy has the best comprehensive performance: the overshoot of knee joint angle control is only 9.7%, and the peak angle error is reduced to 2.1948°; when simulating pathological conditions, the system takes the shortest time to recover stability: 1.068 s for ligament injuries and 0.929 s for meniscus injuries, with maximum response errors below 0.017°. Simulation experiments on healthy subjects showed that the system had a tracking error of ≤5° under two rehabilitation training modes, meeting clinical accuracy requirements, and had good performance in restoring stability under irregular vibration interference. The core contribution of this study is the proposal of the SWO fuzzy PID optimization control strategy, which effectively addresses the shortcomings of existing strategies and significantly improves the control accuracy and anti-interference ability of bionic knee joint robots, providing theoretical support and practical reference for the application of bionic knee joint robots. Full article

This study addresses the problem of actively stabilizing the longitudinal body inclination of a tracked mobile platform operating over uneven terrain. A novel drive system architecture is proposed that combines conventional track traction electric drives with an inertial body-stabilization drive based on a flywheel mounted on the pitch axis between the chassis and the body module. The main contribution of the proposed approach is the coordinated control of the traction drives and the inertial actuator based on a unified dynamic model of the platform. A quadratic performance criterion is formulated, and a coordinated optimal control law is synthesized to limit body angular oscillations while accounting for actuator energy consumption. Simulation results for motion over step-like and random terrain irregularities, as well as under external moment disturbances, demonstrate a significant reduction in both peak and root-mean-square pitch-angle deviations relative to configurations without an inertial actuator and with local body stabilization. The results obtained confirm the potential and effectiveness of inertial stabilization drives as part of coordinated drive control systems for tracked mobile platforms intended for special-purpose applications, and indicate prospects for their use in advanced terrestrial robotic platforms and future space robotic systems operating in challenging environments. Full article

Modern multi-Unmanned Aerial Vehicle (UAV) attacks pose significant challenges to existing counter-UAV frameworks due to their agility, irregular spatial formations, and increasing reliance on intelligent evasive behaviors. This paper proposes a unified interception architecture that integrates Density-Based Spatial Clustering of Applications with Noise (DBSCAN) for multi-target grouping, a deceptive waypoint sequencing (DWS) mechanism for adversarial evasion, and a robust sliding-mode backstepping controller augmented with extended state observers (ESOs) for precise tracking under disturbances. DBSCAN enables real-time clustering of attacking UAVs without prior knowledge of the number of formations, producing dynamic centroids that serve as tactical interception references. To counter risky attackers capable of predicting defender trajectories, a novel DWS strategy introduces centroid-relative waypoints that preserve mission objectives while reducing trajectory predictability. Lyapunov-based analysis is developed for stability, guaranteeing uniform ultimate boundedness of the tracking errors. The proposed approach achieves successful interception in both scenarios, with an interception time of 7 s and final interception error of $0.023$ m in the single-UAV case, and an interception time of 8 s with final interception error of $0.050$ m in the multiple-UAV case, whereas the PID baseline fails to achieve interception under the same conditions. Extensive simulations involving single and multi-cluster engagements demonstrate that the proposed strategy achieves fast, accurate, and deception-resilient interception, outperforming the conventional PID approach in the presence of disturbances, nonlinearities, and dynamic swarm configurations. The obtained results show the effectiveness of integrating adaptive clustering, deceptive planning, and robust nonlinear control for modern UAV–UAV defensive operations. Full article

Nonlinear energy harvesting systems based on multibody structures constitute a promising solution for autonomous devices powered by ambient vibrations. This paper presents the modeling and control of a nonlinear energy harvester employing a double pendulum configuration and BLDC motors operating as generators. The primary objective of the study was to develop a control strategy that enables the maximization of harvested power while simultaneously improving the energy conversion efficiency during the charging of the battery supplying the target system. The developed model incorporates the mechanical equations of motion of the double pendulum, an electrical model of the BLDC motors, and two independently controlled buck–boost converters, each connected to one joint of the pendulum. In addition, a perturb-and-observe (P&O) maximum power point tracking (MPPT) algorithm was implemented, which utilizes a portion of the computational resources of the target system’s microcontroller and allows for dynamic adjustment of the electrical loads seen by the generators. Simulation results obtained in the Simulink environment confirm that the application of independent power converters combined with local MPPT control leads to an increase in the total harvested power and ensures more stable battery charging under conditions of variable mechanical excitation. The obtained results demonstrate the effectiveness of the proposed approach and indicate its potential applicability in self-powered systems operating in environments characterized by irregular and stochastic vibrations. Full article

Electromagnetic levitation control is a core technology for ensuring the stable operation of maglev trains. To enhance the disturbance rejection capability and stability of the levitation system, an IWOA-ISMC control strategy is proposed in this paper. First, a single-electromagnet levitation model with two degrees of freedom is established, in which the effects of spring stiffness and damping are taken into account. Based on this model, an integral sliding mode controller (ISMC) is designed. However, manual parameter tuning based on engineering experience makes it difficult to obtain an optimal parameter combination, and inappropriate controller parameters may lead to significant performance degradation. To address this issue, an improved whale optimization algorithm (IWOA) is introduced to globally optimize the key parameters of the ISMC, resulting in an IWOA-ISMC tailored to the proposed model. Comparative simulations under track irregularity conditions and sudden force disturbances induced by track irregularities are conducted. The results demonstrate that, compared with ISMC, PID, and backstepping controllers, the proposed IWOA-ISMC approach exhibits superior disturbance rejection performance and robustness. Full article

Heart and respiratory rate monitoring during sleep enables the detection of physiological irregularities through contact or contactless methods. Traditional approaches like polysomnography are accurate but costly, ergonomically limited, and often poorly accepted by patients. Smart Bedding^® is a novel, flexible bedsheet equipped with a high-resolution sensor network that records movement, pressure, sound, temperature, and humidity throughout the night. This study aimed to estimate cardiorespiratory parameters using the Smart Bedding^® IMU. Data from 30 participants sleeping on Smart Bedding^® while undergoing simultaneous polysomnography were analyzed. A robust and low-cost preprocessing pipeline was developed; estimation was performed using zero-crossing, peak detection, and Burg’s method for comparison, and validation was conducted using polysomnography as the gold-standard reference. Respiratory and heart rates were accurately estimated, achieving overall accuracies of 93.9% and 88.7% using zero-crossing and peak detection, respectively. Respiratory rate estimation showed no significant limitations across the frequency spectrum or among sleeping positions. However, heart rate estimation accuracy decreased when the frequency was below 55 BPM or when participants slept in a lateral sleep position, likely due to reduced cardiac signal power. Overall, the proposed methodology accurately tracked respiratory and cardiac patterns throughout the night, supporting Smart Bedding^® as a promising tool for future sleep tracking applications. Full article

Background: In forensic ballistics, identifying ammunition types on physical evidence is critical, particularly when metallic residues are minimal. This study comparatively analyzes the elemental signatures deposited by two common projectiles—Full Metal Jacket (FMJ) (Cu/Zn jacket) and Lead Round Nose (LRN) (exposed Pb core)—on complex targets, including pig bone/tissue and mango wood. Methods: Using a semi-automatic handgun at an intermediate range of 5.0 m, residues were examined through high-resolution benchtop Micro-XRF (M4 Tornado) for micro-spatial analysis and Portable XRF (Elio) for rapid field characterization. Additionally, fresh pork leg samples were subjected to a 3-month environmental degradation period to assess trace persistence. Results: Observations indicated that LRN projectiles exhibit markedly elevated Lead (Pb) concentrations along the wound track in bone, hence confirming Pb as a reliable indicator for unjacketed ammunition; specifically, the median Pb concentrations at bullet wiping were 10.39 wt% for M4 and 7.34 wt% for Elio. Conversely, FMJ traces remain strictly confined to the surface bullet wipe area, with median concentrations of Pb, Cu, and Zn being 2.21 wt%, 0.24 wt%, and 0.59 wt% via M4, respectively. Statistical analysis showed a strong correlation for high-concentration elements on tissue, but significantly greater variance on wooden surfaces where FMJ traces exhibited a very weak negative correlation (r = −0.2774) due to minimal and irregular metal transfer. Taphonomic evaluation revealed that the Pb signature from LRN is exceptionally stable (r ≈ 0.9999) even after decomposition, while FMJ signatures are highly sensitive to environmental exposure. Conclusions: This research underscores the necessity of high-sensitivity Micro-XRF (M4) for definitive ammunition verification, providing a refined analytical framework for shooting incident reconstruction even involving degraded remains or complex environmental scenes. Full article

To address the excessive headland space occupation and pronounced vehicle body roll caused by traditional U-shaped turning paths during plant protection sprayer operations in soybean–maize intercropping systems, particularly in fragmented and irregular plots, this study proposes a two-way operation scheme for unmanned sprayers. An improved Reeds–Shepp (RS) curve-based hybrid coverage path planning (CCPP) method is developed to optimize headland turning in non-perpendicular boundary scenarios and generate full-coverage paths for irregular fields. Simulation and field experiments conducted on four plots with an average area of 0.42 had demonstrated that, compared with the conventional U-shaped path, the proposed method reduces the average reserved headland width by 35.21% and shortens the non-operational path length by 21.76%. Under the same path-tracking controller, the turning heading deviation and roll amplitude are reduced by 21.38% and 31.73%, respectively. The results indicate that the improved RS-based path planning method can effectively reduce headland space occupation and enhance the stability and operational efficiency of plant protection sprayers. Full article

Vulcanized NR-SBR is widely used in vehicle components; however, its irreversible crosslinking limits recyclability and contributes to the large number of tires discarded annually worldwide, and in this context, this work presents an experimental comparative assessment of the tribological behavior of conventional tire rubber and silicone VMQ, motivated by a wheel concept based on a detachable tread aimed at improving durability and sustainability rather than proposing an immediate material substitution. Wear and friction behavior were investigated under abrasive and self-friction conditions using pin-on-disk testing with an abrasive counterpart representative of asphalt, supported by optical and scanning electron microscopy. The results show that NR-SBR undergoes severe abrasive and erosive wear, characterized by deep and irregular wear tracks, pronounced fluctuations in the dynamic friction coefficient, and strong sensitivity to load and sliding speed, particularly during the initial stages of track formation. In contrast, VMQ exhibits mild abrasive wear dominated by viscoelastic deformation, leading to shallow and stable wear tracks, lower friction coefficients, and significantly reduced material loss once the contact track is fully developed. These differences are attributed to the distinct mechanical responses of the elastomers, as the higher hardness and limited strain capacity of rubber promote micro-tearing and unstable material removal, while the high elasticity of silicone enables stress redistribution and stable contact conditions under abrasive loading. UV aging increases stiffness of rubber, resulting in reduced wear and friction, while silicone remains largely unaffected after 750 h due to the stability of its Si–O–Si backbone. Self-friction tests further indicate that smooth silicone sliding against rubber yields the lowest friction values, highlighting a favorable material pairing for detachable tread concepts. Factorial design analysis confirms material type as the dominant factor influencing both wear and friction. Overall, for the specific materials and operating conditions investigated, VMQ demonstrates higher durability, greater tribological stability, and improved aging resistance compared to NR-SBR, providing experimental evidence that supports its potential for long-life, more sustainable detachable tread applications. Full article

This work presents the Linear-Region-Based Contour Tracking (LRCT) method for extracting external contours in images, designed to achieve an accurate and efficient description of shapes, particularly useful for archaeological materials with irregular geometries. The approach treats the contour as a discrete signal and analyzes image regions containing edge segments. From these regions, a local linear model is estimated to guide the selection and chaining of representative pixels, yielding a continuous perimeter trajectory. This strategy reduces the amount of data required to describe the contour without compromising shape fidelity. As a case study, the method was applied to images of replicas of archaeological materials exhibiting substantial variations in color and morphology. The results show that the obtained trajectories are comparable in quality to those obtained using classical pipelines based on Canny edge detection followed by Moore tracing, while providing more compact representations well suited for subsequent analyses. Consequently, the method offers an efficient and reproducible alternative for documentation, recording, and morphological comparison, strengthening data-driven approaches in archaeological research. Full article

Irregular wheel wear can significantly degrade wheel–rail interaction performance and, in severe cases, compromise the safety of high-speed trains. Accurate and timely monitoring of wheel wear is crucial for maintaining operational reliability. Existing monitoring methods often rely on high-end sensors or are sensitive to environmental disturbances, limiting their practical deployment. This study proposes a novel method for monitoring irregular wheel wear by analyzing the stator current spectrum of traction motors. Firstly, an electromechanical coupled model is developed by integrating the electric drive system with the vehicle–track dynamic model to capture the propagation of wear-induced excitation. The effect of polygonal wear on the stator current is investigated, revealing the presence of harmonic components coupled with the wear excitation frequency. To extract these features, a comb filter based on Variational Mode Decomposition (VMD) is introduced. The method effectively isolates wheel wear-related harmonics from existing electrical harmonics in the stator current signal. Simulation results demonstrate that the proposed approach can accurately detect harmonic features caused by polygonal wear, validating its applicability. This method provides a feasible and non-intrusive solution for wheel wear monitoring, offering theoretical support for condition-based maintenance of high-speed rail systems. Full article

Motion cueing algorithm (MCA) aims to reproduce the dynamic motion experience of real vehicles for users of driving simulators. Under rough or irregular road conditions, vehicles are subjected to severe shocks and vibrations. However, due to the inherent response delay and limited capability of motion platforms in reproducing high-frequency components, conventional MCA often suffers from slow response and poor tracking accuracy. This mismatch leads to dynamic inconsistency between the visual feedback and the motion cues provided to the driver, which can easily induce discomfort or even aggravate simulator sickness. To address these issues, this study proposes a route-preview MCA based on adaptive model predictive control (RPAMPC). A CNN–LSTM-based vehicle trajectory prediction model is developed by integrating convolutional and recurrent neural networks to exploit forward terrain information. Subsequently, a motion cueing prediction model incorporating actuator stroke and velocity states is formulated, and an AMPC-based MCA is designed to optimize the simulator platform motion under physical constraints. Experimental results on a Stewart motion simulation platform demonstrate that, compared with traditional MCA, the proposed algorithm achieves higher-quality motion cues and significantly reduces sensory errors under complex road conditions. Full article