Search Results (249)

This paper proposes a hierarchical cooperative tracking control method for multi-missile formations under dynamic event-triggered mechanisms, addressing parameter uncertainties and saturated overload constraints. The proposed hierarchical structure consists of a reference-trajectory generator and a trajectory-tracking controller. The reference-trajectory generator considers communication and collaboration among multiple interceptors, imposes saturation constraints on virtual control inputs, and generates reference trajectories for each receptor, effectively suppressing aggressive motions caused by overload saturation. On this basis, a radial basis function neural network (RBFNN) combined with a sliding-mode disturbance observer is adopted to estimate unknown external disturbances and unmodeled dynamics, and the finite-time convergence of the disturbance observer is proved. A tracking controller is then designed to ensure precise tracking of the reference trajectory by missile. This approach not only reduces communication and computational burdens but also effectively avoids Zeno behavior, enhancing the practical feasibility and robustness of the proposed method in engineering applications. The simulation results verify the effectiveness and superiority of the proposed method. Full article

To meet the growing demand for space launches and overcome the limitations of land-based launches, the scientific research community is committed to developing safer and more flexible offshore rocket launch technologies. Their core carriers—marine platforms—are directly exposed to the dynamic and variable marine environment. The complex coupling effects of wind, waves, and currents impose severe challenges upon these platforms, causing complex phenomena such as severe rocking. These phenomena pose severe threats to and significantly interfere with the stability and normal execution of offshore rocket launch operations. This study employs CFD simulation software to analyze liquid sloshing within a cylindrical tank, both with and without baffles. Following validation of the natural frequency, the analysis focuses on the suppression effect of different baffle positions and configurations on tank sloshing. The numerical simulation results indicate the following: Incorporating baffles alters the natural frequency of liquid sloshing within the tank and effectively suppresses the free surface motion. The suppression of the wave surface motion improves as the baffle is positioned closer to the free surface and as the number of perforations in the baffle increases. However, when the number of perforations exceeds a certain threshold, further increasing it yields negligible improvement in the suppression of the sloshing wave surface motion. Full article

Modeling and simulation of aneurysm formation, growth, and rupture plays an essential role in a wide spectrum of application scenarios, ranging from risk stratification to stability prediction, and from clinical decision-making to treatment innovation. Unfortunately, it remains a non-trivial task due to the difficulties imposed by the complex and under-researched pathophysiological mechanisms behind the different development stages of various aneurysms. In this paper, we present a novel computational method for aneurysm simulation using smoothed particle hydrodynamics (SPH). Firstly, we consider blood in a vessel as a kind of incompressible fluid and model its flow dynamics using the SPH method; and then, to simulate aneurysm growth and rupture, the relationship between the aneurysm development and the properties of fluid particles is established by solving the motion control equation. In view of the prevalence of aneurysms in bifurcation vessels, we further enhance the capability of the model by introducing a solution for bifurcation aneurysms simulation according to Murray’s law. In addition, a CUDA parallel computing scheme is also designed to speed up the simulation process. To evaluate the performance of the proposed method, we conduct extensive experiments with different physical parameters associated with morphological characteristics of an aneurysm. The experimental results demonstrate the effectiveness and efficiency of proposed method in modeling and simulating aneurysm formation, growth, and rupture. Full article

A cable-driven hybrid mobile robot is a kind of robot consisting of two modules connected in series, which uses multiple parallel cables to drive the moving platforms. Cable-driven robots benefit from a large workspace, low inertia, excellent dynamic performance due to the lightweight and high extensibility of cables, making them ideal for a wide range of applications, such as sports cameras, large radio telescopes, and planetary exploration. Considering the fundamental dynamic constraint imposed by the unilateral constraint of cables, the workspace and dynamic modeling for cable-driven robots require specialized study. In this paper, a novel cable-driven hybrid robot, which has two motion patterns, is designed, and an arc intersection method for analyzing workspace is applied to solve the robot workspace of two motion patterns. Based on the workspace analysis, a dynamic model for the cable-driven hybrid robot is established, laying the foundation for subsequent trajectory planning. Simulation results in MATLAB R2021a demonstrate that the cable-driven hybrid robot has a large workspace in both motion patterns and is capable of meeting various motion requirements, indicating promising application potential. Full article

Underactuated robotic systems are appealing for industrial use due to their reduced actuator number, which lowers energy consumption and system complexity. Underactuated systems are, however, often affected by residual vibrations. This paper addresses the challenge of generating energy-optimal trajectories while imposing theoretical null residual (and yet practical low) vibration in underactuated systems. The trajectory planning problem is cast as a constrained optimal control problem (OCP) for a two-degree-of-freedom revolute–revolute planar manipulator. The proposed method produces energy-efficient motion while limiting residual vibrations under motor torque limitations. Experiments compare the proposed trajectories to input shaping techniques (ZV, ZVD, NZV, NZVD). Results show energy savings that range from 12% to 69% with comparable and negligible residual oscillations. Full article

This paper presents the development of a fuzzy-PID control able to adapt to several robot–patient interaction modes by monitoring patient evolution during the rehabilitation procedure. This control system is designed to provide targeted rehabilitation therapy through three interaction modes: passive; active–assistive; and resistive. By integrating a fuzzy inference system into the classical PID architecture, the FPID controller dynamically adjusts control gains in response to tracking error and patient effort. The simulation results indicate that, in passive mode, the FPID controller achieves a 32% lower RMSE, reduced overshoot, and a faster settling time compared to the conventional PID. In the active–assistive mode, the FPID demonstrates enhanced responsiveness and reduced error lag when tracking a sinusoidal reference, while in resistive mode, it more effectively compensates for imposed load disturbances. A rehabilitation scenario simulating repeated motion cycles on a healthy subject further confirms that the FPID controller consistently produces a lower overall RMSE and variability. Full article

This study investigated the interplay of bodily degrees of freedom (DoFs) governing the collective variable comprising the center of pressure (CoP) and center of mass (CoM) in postural control through the analytical lens of multiplicative interactions across scales. We employed a task combination involving a wobble board, introducing mechanical instability mainly along the mediolateral (ML) axis and the Trail Making Task (TMT), which imposes precise visual demands primarily along the anteroposterior (AP) axis. Using Multiscale Regression Analysis (MRA), a novel analytical method rooted in Detrended Fluctuation Analysis (DFA), we scrutinized CoP-to-CoM and CoM-to-CoP effects across multiple timescales ranging from $100\mathrm{ms}$ to $10\mathrm{s}$. CoP was computed from ground reaction forces recorded via a force plate, and CoM was derived from full-body 3D motion capture using a biomechanical model. We found that the wobble board attenuated CoM-to-CoP effects across timescales ranging from $100\mathrm{to}400\mathrm{ms}$. Further analysis revealed nuanced changes: while there was an overall reduction, this encompassed an accentuation of CoM-to-CoP effects along the AP axis and a decrease along the ML axis. Importantly, these alterations in CoP’s responses to CoM movements outweighed any nonsignificant effects attributable to the TMT. CoM exhibited no sensitivity to CoP movements, regardless of the visual and mechanical task demands. In addition to identifying the characteristic timescales associated with bodily DoFs in facilitating upright posture, our findings underscore the critical significance of directionally challenging biomechanical constraints, particularly evident in the amplification of CoP-to-CoM effects along the AP axis in response to ML instability. These results underscore the potential of wobble board training to enhance the coordinative and compensatory responses of bodily DoFs to the shifting CoM by prompting appropriate adjustments in CoP, thereby suggesting their application for reinstating healthy CoM–CoP dynamics in clinical populations with postural deficits. Full article

As the urban underground natural gas pipeline network expands, the explosion risk arising from methane accumulation in drainage ditches due to pipeline leakage has increased severely. A two-dimensional numerical model—9.7 m in length (including a 1-m obstacle section), 0.1 m in diameter, and with a water volume fraction of 0.2—was developed to address the flexible boundary characteristics of urban underground ditches. The investigation examined the influence of methane concentration on explosion propagation characteristics. Results indicated that, at a methane concentration of 11%, the peak pressure attained 157.9 kPa, and the peak temperature exceeded 3100 K—all of which were significantly higher than the corresponding values at 10%, 13%, and 16% concentrations. Explosion-induced water motion exerted a cooling effect that inhibited heat and pressure transfer, while obstacles imposed partial restrictions on flame propagation. Temporal profiles of temperature and pressure exhibited three distinct stages: “initial stability–rapid rise–attenuation”. Notably, at a methane concentration of 16%, the water column formed by fluid vibration demonstrated a pronounced cooling effect, causing faster decreases in measured temperatures and pressures compared to other concentrations. Full article

This study investigates a stochastic production planning problem with regime-switching parameters, inspired by economic cycles impacting production and inventory costs. The model considers types of goods and employs a Markov chain to capture probabilistic regime transitions, coupled with a multidimensional Brownian motion representing stochastic demand dynamics. The production and inventory cost optimization problem is formulated as a quadratic cost functional, with the solution characterized by a regime-dependent system of elliptic partial differential equations (PDEs). Numerical solutions to the PDE system are computed using a monotone iteration algorithm, enabling quantitative analysis. Sensitivity analysis and model risk evaluation illustrate the effects of regime-dependent volatility, holding costs, and discount factors, revealing the conservative bias of regime-switching models when compared to static alternatives. Practical implications include optimizing production strategies under fluctuating economic conditions and exploring future extensions such as correlated Brownian dynamics, non-quadratic cost functions, and geometric inventory frameworks. In contrast to earlier studies that imposed static or overly simplified regime-switching assumptions, our work presents a fully integrated framework—combining optimal control theory, a regime-dependent system of elliptic PDEs, and comprehensive numerical and sensitivity analyses—to more accurately capture the complex stochastic dynamics of production planning and thereby deliver enhanced, actionable insights for modern manufacturing environments. Full article

Fluids that exhibit self-rewetting properties, such as aqueous long-chain alcohol solutions, display a unique quadratic relationship between surface tension and temperature and are marked by a positive gradient. This characteristic leads to distinctive patterns of thermocapillary convection and associated interfacial dynamics, setting self-rewetting fluids apart from normal fluids (NFs). The potential to improve heat transfer using self-rewetting fluids (SRFs) is garnering interest for use in various technologies, including low-gravity conditions and microfluidic systems. Our research aims to shed light on the contrasting behaviors of SRFs in comparison to NFs regarding interfacial transport phenomena. This study focuses on the thermocapillary convection in SRF layers with a deformable interface enclosed inside a closed container modeled as a square cavity, which is subject to nonuniform heating, represented using a Gaussian profile for the heat flux variation on one of its sides, in the absence of gravity. To achieve this, we have enhanced a central-moment-based lattice Boltzmann method (LBM) utilizing three distribution functions for tracking interfaces, computing two-fluid motions with temperature-dependent surface tension and energy transport, respectively. Through numerical simulations, the impacts of several characteristic parameters, including the viscosity and thermal conductivity ratios, as well as the surface tension–temperature sensitivity parameters, on the distribution and magnitude of the thermocapillary-driven motion are examined. In contrast to that in NFs, the counter-rotating pair of vortices generated in the SRF layers, due to the surface tension gradient at the interface, is found to be directed toward the SRF layers’ hotter zones. Significant interfacial deformations are observed, especially when there are contrasts in the viscosities of the SRF layers. The thermocapillary convection is found to be enhanced if the bottom SRF layer has a higher thermal conductivity or viscosity than that of the top layer or when distributed, rather than localized, heating is applied. Furthermore, the higher the magnitude of the effect of the dimensionless quadratic surface tension sensitivity coefficient on the temperature, or of the effect of the imposed heat flux, the greater the peak interfacial velocity current generated due to the Marangoni stresses. In addition, an examination of the Nusselt number profiles reveals significant redistribution of the heat transfer rates in the SRF layers due to concomitant nonlinear thermocapillary effects. Full article

This study investigates the external load and positional constraints’ impact on the accuracy and performance of an autonomous adaptive electrohydraulic actuator with pump control intended for mobile equipment. An actuator simulation model was developed in the MATLAB/Simulink (version R2021A) environment, and a full-scale experimental setup was constructed to validate this model. Various motion trajectories under different load conditions were analyzed to evaluate discrepancies between simulated and experimental results and to identify key performance characteristics across operational modes. The results demonstrate that the simulation model adequately replicates the actuator’s dynamic behavior, although deviations emerge under high-load conditions. Notably, in the absence of external load, the static positioning error does not exceed 0.025 mm (0.05% of the 50 mm target value), while under the maximum load of 8000 N, the error increases to 0.075 mm (0.15% of the 50 mm target value). These limitations are primarily due to current constraints imposed by the actuator’s power supply capacity (up to 300 W at 24 V), which restrict pressure buildup rates under heavy loads. Nevertheless, the proposed control system exhibits robustness to load variations and ensures positioning accuracy within acceptable limits, demonstrating its practical suitability for mobile machinery applications. The developed simulation model also serves as a valuable tool for control system tuning and testing in the absence of a physical prototype. Full article

Offshore cranes equipped with active motion compensation (AMC) systems play a vital role in marine engineering tasks such as offshore wind turbine maintenance, subsea operations, and dynamic load positioning under wave-induced disturbances. These systems rely on complex hydraulic actuators whose strongly nonlinear dynamics—often described by differential-algebraic equations (DAEs)—impose significant computational burdens, particularly in real-time applications like hardware-in-the-loop (HIL) simulation, digital twins, and model predictive control. To address this bottleneck, we propose a neural network-based surrogate model that approximates the actuator dynamics with high accuracy and low computational cost. By approximately reducing the original DAE model, we obtain a lower-dimensional ordinary differential equations (ODEs) representation, which serves as the foundation for training. The surrogate model includes three hidden layers, demonstrating strong fitting capabilities for the highly nonlinear characteristics of hydraulic systems. Bayesian regularization is adopted to train the surrogate model, effectively preventing overfitting. Simulation experiments verify that the surrogate model reduces the solving time by 95.33%, and the absolute pressure errors for chambers $p_1$ and $p_2$ are controlled within 0.1001 MPa and 0.0093 MPa, respectively. This efficient and scalable surrogate modeling framework possesses significant potential for integrating high-fidelity hydraulic actuator models into real-time digital and control systems for offshore applications. Full article

This study presents a novel semi-submersible platform design for 10 MW vertical-axis wind turbines (VAWTs), specifically engineered to address the compounded challenges of China’s intermediate-depth (40 m), typhoon-prone maritime environment. Unlike conventional horizontal-axis configurations, VAWTs impose unique demands due to omnidirectional wind reception, high aerodynamic load fluctuations, and substantial self-weight—factors exacerbated by short installation windows and complex hydrodynamic interactions. Through systematic scheme demonstration, we establish the optimal four-column configuration, resolving critical limitations of existing concepts in terms of water depth adaptability, stability, and fabrication economics. The integrated design features central turbine mounting, hexagonal pontoons for enhanced damping, and optimized ballast distribution, achieving a 3400-tonne steel mass (29% reduction vs. benchmarks). Comprehensive performance validation confirms exceptional survivability under 50-year typhoon conditions (Hs = 4.42 m, Uw = 54 m/s), limiting platform tilt to 8.02° (53% of allowable) and nacelle accelerations to 0.10 g (17% of structural limit). Hydrodynamic analysis reveals heave/pitch natural periods > 20 s, avoiding wave resonance (Tp = 7.64 s), while comparative assessment demonstrates 33% lower pitch RAOs than leading horizontal-axis platforms. The design achieves unprecedented synergy of typhoon resilience, motion performance, and cost-efficiency—validated by 29% steel savings—providing a technically and economically viable solution for megawatt-scale VAWT deployment in challenging seas. Full article

Electromyography (EMG) signals have diverse applications, ranging from prosthetic hands and assistive suits to rehabilitation devices. Nonetheless, their performance suffers from cross-subject generalization issues, electrode shifts, and daily variability. In a previous study, while transfer learning narrowed the classification performance gap to −1% in an eight-class scenario under electrode shift, they imposed the burden of additional data collection and re-training. To address this issue in real-time prediction, we investigated a sliding-window normalization (SWN) technique that merges z-score normalization with sliding-window processing to align the EMG amplitude across channels and mitigate the performance degradation caused by electrode displacement. We validated SWN using experimental data from a right-arm trajectory-tracking task involving three motion classes (rest, flexion, and extension of the elbow). Offline analysis revealed that SWN mitigated accuracy degradation to −1.0% without additional data for re-training or multi-condition training, a 6.6% improvement compared with the −7.6% baseline without normalization. The advantage of SWN is that it operates with data from a single electrode position for training, which eliminates both the collection of multi-position training data and the calibration of deep learning models before practical use in EMG applications. Moreover, combining SWN with multi-position training exceeded the classification accuracy of the no-shift condition by 2.4%. Full article

A semi-analytical investigation is conducted to examine the coupled translational and rotational motions of a composite spherical particle (consisting of an impermeable hard core surrounded by a permeable porous shell) immersed in a viscous fluid parallel to one or two planar boundaries under the steady condition of a low Reynolds number. The fluid flow is described using the Stokes equations outside the porous shell and the Brinkman equation within it. A general solution is formulated by employing fundamental solutions in both spherical and Cartesian coordinate systems. The boundary conditions on the planar walls are implemented using the Fourier transform method, while those on the inner and outer boundaries of the porous shell are applied via a collocation technique. Numerical calculations yield hydrodynamic force and torque results with good convergence across a broad range of physical parameters. For validation, the results corresponding to an impermeable hard sphere parallel to one or two planar walls are shown to be in close agreement with established solutions from the literature. The hydrodynamic drag force and torque experienced by the composite particle increase steadily with larger values of the ratio of the particle radius to the porous shell’s permeation length, the ratio of the core radius to the total particle radius, and the separations between the particle and the walls. It has been observed that the influence of the walls on translational motion is significantly stronger than that on rotational motion. When comparing motions parallel versus normal to the walls, the planar boundaries impose weaker hydrodynamic forces but stronger torques during parallel motions. The coupling between the translation and rotation of the composite sphere parallel to the walls exhibits complex behavior that does not vary monotonically with changes in system parameters. Full article