Search Results (483)

Benthic AUVs (underwater quadruped robots) merge the cruising efficiency of submersibles with the bottom-crawling stability of legged robots for unstructured deep-sea exploration. However, the deliberate separation of the center of gravity and buoyancy—essential for static stability—generates a significant righting moment. When climbing steep slopes, this moment resists hull alignment. If the slope exceeds the robot’s maximum hydrostatic pitch limit, conventional inverse kinematics algorithms fail: the hind legs lose ground contact and propulsion is lost. To overcome this, this paper proposes a framework integrating optimal force distribution, adaptive trajectory probing, and admittance control. An analytical multi-point moment balance model derives the terrain-adaptive pitch boundaries. A Quadratic Program (QP) then distributes contact forces, tasking front legs with stabilizing the righting moment while hind legs provide thrust. During the swing phase, adaptive Bezier sequences prevent anterior slope collisions and ensure posterior ground contact. Furthermore, a Cartesian admittance controller provides active compliance to manage the nonlinear friction of dynamic waterproof seals. Validated via a high-fidelity physics-based simulation model calibrated against physical pool trials, the robot achieved robust traversal of $15°$ and $33°$ steep slopes. Statistical robustness is substantiated via a 30-trial Monte Carlo study, where postural stability remained remarkably consistent with a mean Pitch RMSE of $2.88°$ across a $\pm 10\%$ parameter uncertainty envelope. Compared to traditional baseline algorithms, the proposed method successfully suppressed torque chattering by $54.1\%$ in the high-frequency band (2–$50\mathrm{Hz}$) and improved energetic efficiency by up to $43\%$ on steep gradients. These findings offer a validated control architecture for heavy-duty deep-sea platforms navigating complex benthic topographies. Full article

Falls in older adults and individuals with balance impairments remain a major concern because they are closely associated with injury, reduced mobility, and loss of independence. This study presents a preclinical proof-of-concept for a cognitive smart walker architecture that combines user-compatible walking assistance with active safety intervention. The system integrates a 2D LiDAR sensor for contactless lower-limb monitoring, a six-degree-of-freedom (6-DOF) force/torque sensor to measure user–walker interaction, and an inertial measurement unit (IMU) for dynamic monitoring, with all data processed in real time on a Raspberry Pi/ROS-based platform. Normal walking assistance is provided through a command-level variable admittance-based controller that converts interaction forces into a smoothed signed duty-cycle command rather than a rigid speed-control signal. Safety decisions are managed by a Hierarchical State Machine (HSM). Early-risk conditions are handled through motor-based dynamic braking, whereas severe physical crises additionally deploy lateral support legs to enlarge the base of support. Within this framework, the system can detect and manage foot entanglement, grip loss, forward fall, vertical collapse, lateral fall, successive crises, and recovery-abort events. In experiments across multiple scenarios, the system correctly detected all 50 crisis cases and did not issue unnecessary interventions in 30 non-crisis cases. These findings show that the proposed architecture can preserve transparent walking assistance during normal gait while providing graded, context-sensitive active safety when risk emerges. Full article

The tectonic setting of Taiwan and its surrounding regions is characterized by the complex interaction between the northwest-oriented Ryukyu subduction zone and the east-oriented Manila subduction zone. Within this subduction framework, the elastic thickness of the lithosphere (Te) serves as a critical parameter for elucidating the mechanical behavior of the area. In this study, we employed the admittance–correlation method to estimate Te values across Taiwan and adjacent territories. The findings indicate that sedimentary loading results in an overestimation of the maximum Te by approximately 50 km; after adjustment, the Te values range from 0 to 60 km throughout the study area. On Taiwan, Te values predominantly lie between 20 and 30 km, decreasing to 10–20 km near the margins adjacent to the Ryukyu and Manila subduction fronts. The Philippine Sea Plate exhibits comparatively higher Te values, ranging from 40 to 65 km. The spatial distribution of Te broadly corresponds with major tectonic subdivisions. Statistical analyses reveal a weak negative correlation between Te and surface heat flow (r = −0.44) and a weak positive correlation with shear-wave velocity anomalies at a depth of 100 km (r = 0.22), suggesting that the thermal structure exerts only a moderate influence on lithospheric strength in this region. Nonetheless, within oceanic crustal domains, the relationship between Te and oceanic crustal age largely adheres to models of crustal cooling and lithospheric thickening, consistent with isotherm depths of approximately 200–400 °C. Additionally, dynamic topography associated with slab subduction may locally diminish Te by up to 25 km. Cross-sectional profiles through northern Taiwan and the Philippine Sea block reveal pronounced coupling between subduction geometry and Te distribution. The observed spatial patterns of Te reflect the mechanical imprint of prolonged tectonic evolution, with the orientation of Te gradients generally aligned with the direction of maximum principal compressive stress. Collectively, these results suggest that subduction geometry and tectonic processes are important factors influencing the spatial variability and evolutionary trajectory of lithospheric strength in Taiwan and its environs. Full article

This paper presents a fuzzy-based adaptive admittance control (FAAC) framework for position-controlled robots in uncertain contact environments. The proposed FAAC regulates admittance parameters using three fuzzy adaptation maps rather than directly generating robot control inputs. The Mass-Adaptation Fuzzy Map (MAFM) adjusts the dominant virtual mass eigenvalue, the Damper–Mass Ratio Fuzzy Map (DMRFM) adapts the damping-related ratio, and the Rendering-Quality Supervisory Fuzzy Map (RQ-SFM) restricts unsafe low-mass adaptation based on rendering quality and vibration metrics. An energy-tank-based admissibility filter is integrated to preserve passivity during online parameter adaptation and contact transitions. Comparative simulations against a stiffness-adaptive baseline and an ablated mass–damping adaptive baseline under nominal, noisy, and filtered sensing conditions verify the robustness of the proposed architecture. Experiments on a UR10 polishing task further show that the proposed FAAC improves force-tracking consistency and contact-maintenance robustness compared with fixed-parameter AAC baselines and FAAC-M. In particular, the proposed FAAC achieved the lowest force standard deviation of 2.76 N and no contact-loss events, whereas the baseline AAC controllers exhibited force fluctuations associated with abrupt desired stiffness changes during contact. These results demonstrate the effectiveness of FAAC for robust robot–environment interaction under uncertain contact conditions. Full article

A large number of grid-connected inverters have been connected to distribution networks and can be used to mitigate harmonics at the system level. Deploying distributed power electronic devices for harmonic mitigation is a cost-effective solution for distribution networks. However, existing coordination methods typically depend on highly reliable, low-latency communications. Communication delays or interruptions can significantly degrade coordination performance and even exacerbate harmonic distortion. This paper presents a hierarchical, coordinated harmonic compensation method for multiple multifunctional grid-tied inverters (MFGTIs). At the primary control level, harmonic domain virtual admittance is incorporated, enabling each device to adaptively inject harmonic compensation currents using only local measurements, maintaining baseline compensation capability when communication is limited or interrupted. At the secondary control level, a distributed model predictive control (DMPC) scheme is derived from the harmonic steady-state equivalent circuit. The virtual admittance parameters are updated iteratively using measurements exchanged only among neighboring nodes, enabling coordinated sharing of compensation currents without requiring global information or frequent harmonic power flow calculations. Case studies demonstrate that the proposed method reduces nodal harmonic voltages under communication constrained conditions while significantly lowering the computational burden. Full article

This study proposes a model predictive control (MPC)-based Assist-as-Needed (AAN) strategy for upper-limb rehabilitation robots, with particular emphasis on mitigating motor slacking. In conventional error-based AAN approaches, robotic assistance is regulated through a single coefficient tied to the tracking error; thus, a reduction in voluntary effort is absorbed into the assistive channel and remains obscured by a small tracking error. The proposed method decouples this mechanism by introducing a two-channel admittance structure, in which the robotic-assistance gain $A_k$ and the user-participation-reflection gain $B_k$ are jointly optimized within a single convex MPC formulation. The cost function addresses trajectory tracking, participation-aware force alignment, assistance suppression, and passivity, enforced through energy-tank constraints. The controller was validated in two experiments on a mobile upper-limb rehabilitation robot. The first experiment confirmed differential adaptation of $A_k$ and $B_k$ across three instructed contribution levels, with the participation ratio increasing from 0.103 to 0.879 as the contribution shifted from insufficient to appropriate. The second experiment compared the controller with an error-based AAN baseline and a forgetting-factor AAN baseline under an induced motor-slacking condition, in which the task-direction contribution was reduced to 45%. Under an identical synthesized input, the proposed controller yielded a lower aggregate human-contribution ratio of 0.282, compared with 0.595 and 0.535 for the two baselines, respectively. This indicates that the externally imposed reduction in participation was represented more explicitly in the controller allocation, rather than being masked by error-driven assistive compensation. These results suggest that the proposed approach extends AAN control toward a participation-preserving, anti-slacking strategy for robot-assisted rehabilitation. Full article

This study examined relationships between electrical parameters, namely impedance (Z), admittance (Y), parallel capacitance (Cp), and series capacitance (Cs), and beef tenderness in the semimembranosus muscle during ageing for 3, 7, 14, and 28 days at 4 ± 1 °C. It also assessed selected compositional traits after 14 days. The effects of electrode configuration and signal frequency on measurement sensitivity were evaluated. Beef from Holstein–Friesian bulls (n = 8) representing two feeding treatments was used. Electrical measurements were performed with an in-house sensor and an LCR-based system. Two electrode configurations were applied: T, across the muscle fibres, and L, along the fibres. pH, Warner–Bratzler shear force (WBSF), and cooking loss were determined during ageing. Chemical composition and fatty acid profile were analysed after 14 days. WBSF decreased during ageing, whereas cooking loss showed a non-linear pattern, increasing up to day 14 and decreasing after 28 days. Electrical parameters were strongly affected by frequency and electrode configuration. After 14 days of ageing, the strongest relationship with tenderness was found for Z in the T configuration at 1 kHz (r = −0.834). The T configuration better reflected moisture content and fatty acid groups, whereas the L configuration was more informative for ash. Cs provided additional information related to protein. These findings indicate the potential usefulness of this approach for rapid beef quality screening under strictly standardised measurement conditions, although the observed relationships require confirmation in a larger sample set. Full article

With the advancement of computing and transmission technologies, there has been a growing demand for quartz oscillators and resonators, whose performance is evaluated by the quality coefficient (Figure of Merit, FoM). High-frequency, miniaturized fabrication is the design goal, and process optimization and innovative design methods need to be emphasized. Based on the 1978 Institute of Electrical and Electronics Engineers standard definition, the old design parameters of AT-cut quartz crystal sheet are retained to analyze the structural loss factor, dielectric loss factor, frequency, admittance, quality factor, and error value with the fundamental frequency increased from 76.8 to 96 MHz. In this study, COMSOL Multiphysics is used to simulate and analyze the quartz resonator by introducing the femtosecond laser quartz microvia machining technique from the literature, improving the electrode and inverted wet etching process, and incorporating the structural loss factor and dielectric loss factor into the quartz resonator model to observe the changes in the quality factor, the percentage of the quality factor error, and the values of the eigen-frequency and the error of the frequency. We analyze the trend of loss factor, frequency value, and error value and analyze the process advantages and disadvantages of femtosecond laser drilling electrodes, coated electrodes, inverted wet etching, inverted dry etching, and single-side and double-side etching to provide a reference for the design of future process components. Full article

In the context of Industry 5.0, human–robot collaboration increasingly demands intuitive, safe, and sensorless interaction for tasks such as hand-guided teaching and concurrent manipulation. However, conventional admittance control systems are prone to instability due to abrupt changes in human arm stiffness and their reliance on accurate dynamic models. To address these challenges, this paper proposes a sensorless external force estimation and variable admittance control method that models robot dynamic uncertainties and interaction forces as normally distributed stochastic quantities. An improved particle swarm optimization algorithm is introduced to calibrate the variance parameters, enhancing estimation accuracy and robustness. Furthermore, an energy-based variable admittance control strategy is developed, which preserves system passivity by adaptively adjusting inertia and damping gains based on real-time energy variations. The proposed method was validated on a redundant robot platform. Experimental results show that the external force and torque estimation errors remain below 3 N and 3 N.m, respectively, with lower detection delays and errors than those of a first-order generalized momentum observer in collision detection. Variable admittance experiments demonstrate that the system maintains passivity and stable interaction even under sudden arm stiffness changes. The approach is well-suited for industrial applications requiring safe, sensorless, and compliant human–robot collaboration. Full article

Background/Objectives: In addition to the clinical gold standard, tympanometry, several alternatives for middle ear diagnostics have evolved over the past decades. With the so-called pressureless acoustic impedance test, the Neuranix Medwave, another device, came into play. Methods: Using a retrospective, anonymous study design, descriptive data were reported, and the correlation between Medwave’s results and tympanometry types was evaluated. Also, the correlation between the patients’ age and the Medwave resulting parameters was evaluated. We were able to show changes in the measurement results over time in the case of paracentesis and tube insertion. Results: The analyzed data show that it is possible to differentiate between tympanometry result type A and type B using the Medwave resulting parameter resonance frequency (“fR”), but not when using peak admittance (“P”). Between all other types, it was not possible to differentiate using the Medwave resulting parameters, nor fR nor P. Due to the low statistical power, this may be due to a type II error. Regarding age, a correlation was found only for the tympanometry result type A. The case over time showed a clear difference in the affected ear between the time before and after the ear surgeries, as well as the contralateral healthy ear. Conclusions: While this study indicates the potential use of the PLAI technology, especially as a tool in situations where traditional tympanometry is not feasible, the results need to be interpreted with caution. Further validation with larger and more balanced groups of participants is necessary to confirm these initial findings and to more clearly define the clinical utility of this technology. Full article

This paper presents a systematic methodology for time-domain modeling of three-phase power transformers aimed at electromagnetic transient analysis in shipboard and embedded electrical systems. Accurate modeling of transformers in such environments is critical, as naval power systems are subject to strict electromagnetic compatibility (EMC) requirements and are particularly susceptible to fast transients caused by switching operations, fault events, and nonlinear loads operating in confined and isolated grids. The proposed approach combines the Vector Fitting (VF) algorithm with Clarke modal decomposition to obtain stable, passive, and causal rational approximations of the frequency-dependent admittance matrix over a wide frequency range. The admittance matrix is first identified from frequency-domain measurements or simulations, capturing the transformer’s terminal behavior across multiple frequency sub-bands. Clarke’s transformation is then applied to decouple the three-phase system into independent modal components—namely the zero-sequence and positive-sequence modes, reducing the original multi-phase problem to a set of independent single-phase systems. This modal decoupling significantly improves computational efficiency without sacrificing accuracy, as each mode can be fitted and simulated independently. Full article

The synchronous continuum robot (SCR) was developed to emulate biological structures, such as animal tails and elephant trunks, based on continuum robot principles. By synchronizing disk motions, the SCR generates biologically inspired continuous movements while maintaining precise trajectory control. However, its synchronization-based architecture limits adaptability during physical interaction due to rigid trajectory-following characteristics. To address this limitation, this paper proposes a sensorless variable admittance control (VAC)-based compliant motion generation framework for the SCR. A dynamic model-based sensorless disturbance observer is designed to estimate external torques without additional force sensors. To compensate for uncertainties inherent in the cable-driven transmission mechanism, an adaptive term is incorporated into the parameter identification process, improving disturbance estimation accuracy. Based on the estimated external torques, admittance parameters are adaptively modulated according to joint angles, angular velocities, and robot posture, enabling interaction-aware motion speed regulation. Furthermore, the proposed method simultaneously enforces constraints on both joint angles and angular velocities through the adaptive regulation of target positions and velocities, ensuring safe and physically feasible motion. Experimental results under various interaction scenarios demonstrate reliable contact-independent force estimation and effective compliant motion generation. The proposed framework provides an integrated solution for robust force estimation, adaptive compliance control, and simultaneous constraint enforcement in mechanically synchronized continuum robots. Full article

The paper presents SFPD, the new open algorithm developed by the University of Padova (PD in the acronym) for computing the steady-state regime due to any number of simultaneous faults (SF at the beginning of the acronym) both short circuits and open conductors. The algorithm does not have simplified hypotheses, since it benefits from the pre-fault regime based on PFPD_MCA (power flow by University of Padova with multiconductor cell analysis), a multiconductor power flow (developed and published by the first author) which takes into account both the active conductors (i.e., the phases subjected to the impressed voltages) and the passive conductors (i.e., the interfered metallic conductors, namely earth wires of overhead lines, metallic screens and armors of land and submarine cables, enclosures of gas insulated lines, return and earth wires of 2 × 25 kV AC high-speed railway supply system, etc.). Different types of faults are considered, and where they occur (also along the lines), by means of a suitable admittance matrix in phase frame of reference and embedded inside the overall network bus admittance matrix. Some comparisons with simplified approaches are presented in order to demonstrate the power of the method. Eventually, application to the real Italian network is comprehensively shown. Full article

This work develops a zero-trust, physics-constrained mathematical framework for detecting stealthy drift perturbations in power system dynamical models. Such perturbations constitute adversarial, statistical deviations that preserve first-order operating trends, making them difficult to identify using classical residual-based estimators or unconstrained data-driven models. We introduce ZETWIN, a spatio-temporal learning architecture formulated as a constrained optimization problem in which the nodal admittance matrix $Y_{bus}$ acts as a graph-structured linear operator embedded directly into the loss functional. This construction enforces Kirchhoff-consistent latent representations and yields a mathematically grounded zero-trust decision rule that flags any trajectory violating physical feasibility, independent of prior attack signatures. The proposed framework is evaluated using a PyPSA-based AC–DC meshed network, demonstrating an AUROC = 0.994, and F1 = 0.969. The formulation highlights how physics-informed constraints, graph operators, and spatio-temporal approximation theory can be combined to construct mathematically interpretable zero-trust detectors for complex dynamical systems. Full article

With the growing significance of renewable energy resources and energy storage systems, the number of grid-connected inverters has been rising at an increasingly rapid pace. Generally, these inverters are directly integrated with the distribution network by synchronizing with the grid voltage at the point of common coupling. However, the low grid strength and varying R/X ratios, as the common characteristics of most distribution networks or weak grids, can lead to dynamic interactions that comprise stability and limit the power transfer capacity of grid-connected inverters. To ensure stable operation of the inverters, researchers must determine the stability boundary, described as the maximum power transfer capacity of grid-connected inverters under the premise of maintaining system small-signal stability. For this purpose, we propose to formulate a state-space model of the system in the synchronously rotating dq-frame of reference and perform eigenvalue analysis to determine the stability boundary. With a detailed model of the control structure and parameters of the grid-connected inverters, the stability boundary is identified as a surface with respect to different grid strengths and R/X ratios. Case study results of proposed eigenvalue analysis are compared with those of admittance model-based stability analysis as well as time-domain simulation using a switching model in Matlab/Simulink, validating the effectiveness and accuracy of the proposed eigenvalue analysis for stability boundary identification. Full article