Search Results (157)

Rapid advances in on-orbit servicing technologies have driven exponential growth in micro-spacecraft on-orbit ejection missions. Post-separation attitude disturbances are the dominant factor determining mission success, requiring accurate and rapid disturbance prediction. This study develops an efficient multi-rigid-body dynamic simulation framework for on-orbit ejection based on the simulation software ADAMS. Contact parameters between the micro-spacecraft and guide rail are calibrated against high-fidelity rigid–flexible coupled simulation results from the simulation software LS-DYNA, establishing a streamlined simulation pipeline. Using this validated framework, the effects of thrust misalignment angle, thrust eccentricity, and mass eccentricity on ejection-phase attitude disturbances are systematically quantified. Results demonstrate that the calibrated ADAMS multi-rigid-body model effectively substitutes computationally intensive rigid–flexible coupled models without sacrificing predictive accuracy. Specifically, constraining the axial thrust misalignment angle to ≤0.2°, axial thrust eccentricity to ≤0.4 mm, and axial mass eccentricity to ≤0.2 mm can significantly enhance separation attitude stability. This work provides a practical and efficient engineering methodology for the rapid assessment of attitude disturbances in micro-spacecraft on-orbit ejection systems. However, this study is limited to analyzing the ejection phase of separation, neglecting attitude disturbance effects in the subsequent orbital flight and target impact phases. Future work will address these omissions by extending the model to the entire mission profile and quantifying associated uncertainties. Full article

Modular Mobile Robotic Systems (MMRSs) require simulation tools capable of supporting distributed control architectures, dynamic reconfiguration, and scalable experimentation. This work evaluates three complementary simulation strategies for a homogeneous MMRS composed of autonomous Two-Wheel Inverted Pendulum (TWIP) modules: (i) Webots, selected for rapid prototyping through its integrated GUI; (ii) Pinocchio, paired with the Jiminy simulator to enable modern rigid-body dynamics and control-oriented modeling; and (iii) PyBullet, chosen for programmatic flexibility and reinforcement learning (RL) compatibility. A minimal and controlled benchmark scenario was implemented across all platforms to isolate core simulation characteristics: two differentially driven robots were coupled using the most appropriate mechanism available in each environment and simulated for 1000 steps in headless mode while monitoring CPU usage, memory consumption, and execution time. In addition, a feature-based analysis focused on MMRS-relevant requirements, including dynamic reconfiguration, multi-agent scalability, and suitability for RL workflows. Full article

To address fault diagnosis under limited sample conditions, this paper proposes a small-sample diagnosis framework integrating multibody dynamic modeling and a GAN–CNN fusion strategy. First, a rigid–flexible coupled multibody dynamic model of the reducer is established to simulate vibration responses under typical fault modes, including broken gear tooth, gear wear, and bearing outer ring fault, thereby generating representative simulation samples. Second, to reduce the distribution discrepancy between simulated and measured data, the simulated samples are introduced into a generative adversarial learning framework for feature enhancement, with limited measured samples used as references. Cosine similarity is employed to evaluate the consistency between the enhanced simulated data and the measured data in the feature space. Finally, the enhanced simulated samples are fused with measured samples to construct a hybrid dataset for convolutional neural network training and fault classification. Experimental results show that the proposed framework improves the similarity between simulated and measured data, with cosine similarity increasing from below 0.65 to above 0.80. Under small-sample conditions, the mean diagnosis accuracy reaches 83.81%, which is 17.33 percentage points higher than that obtained using the original small-sample dataset. The proposed framework provides an effective modeling and algorithmic approach for reducer fault diagnosis under data-scarce conditions. Full article

This paper aims to develop an on-board shock absorber detection method for general aviation aircraft. The effects of common gas and oleo leakage are analyzed in this paper. Based on the principle of landing gear dynamics, it is found that gas leakage and oleo leakage would mainly affect air spring force of shock absorbers in various ways. A rigid–flexible coupled landing gear multi-body system (MBS) model is developed by considering strut flexibility, aiming to offer more accurate simulated responses. A database is developed that considers common leakage faults and typical landing conditions using the developed landing gear model. A deep learning model is proposed in this paper. The proposed model is trained and tested using the database simulated from the rigid–flexible coupling landing gear model. The proposed method demonstrates robust detection performance, achieving over 95% precision for most fault types. This work provides a practical, sensor-efficient solution for real-time health monitoring of landing gear shock absorbers, contributing to improved maintenance strategies and operational safety for general aviation aircraft. As this is a preliminary feasibility study, full validation requires future drop tests or instrumented flight tests. Full article

Extreme orbital thermal cycling and temperature-dependent clearance nonlinearity make it difficult to predict contact–impact, stick–slip, and bifurcation responses of flexible deployable space structures with sufficient stability, accuracy, and computational efficiency. An Adaptive Dissipation–Precision Coordinated Multi-Scale Implicit Integration Algorithm (ADPC-MSIIA) is proposed. First, an absolute nodal coordinate formulation (ANCF)-based thermo-mechanical clearance-joint model with thermal-viscosity-modified contact and frictional/impact heat feedback is established; second, a dual-time-scale implicit integration scheme with dual-$\alpha$ stability–dissipation control and third-order compensation is developed; finally, numerical validation is performed using a linear single-degree-of-freedom (SDOF) benchmark, a temperature-dependent clearance impact oscillator, finite-element and published benchmark comparisons, and a deployable annular truss antenna case. Simulation results show that ADPC-MSIIA achieves a high-frequency spectral radius of $0.867$, an effective convergence order of $2.98$, a maximum contact force error of $3.1\%$, and a $51.7\%$ reduction in the global cumulative error compared with the generalized-$\alpha$ method. This study contributes to knowledge by linking temperature-driven clearance evolution, frictional heat feedback, and adaptive numerical dissipation within a unified framework for predicting non-smooth thermo-mechanical deployment dynamics of large flexible space structures with clearance joints. Full article

Conventional quadruped robots are usually built with a rigid body, whereas quadrupedal mammals have flexible spines to perform agile behaviours on rough terrains. Applying a flexible spine to robots is a promising way to achieve dynamic and stable movement in extreme environments. In this paper, a novel bio-inspired spine constructed with a tensegrity structure is introduced. The prototype of the spine includes active and passive parts that can both be actively actuated and passively compliant. It has two joints with three degrees of freedom (DOF) each and can generate complex and multi-degree motions simultaneously. To control the spine with adjustable stiffness, a method based on vector closure and adjustment of pretension ratio is proposed. Several experiments are reported to illustrate the physical design of the spine and demonstrate the properties of the spine. The results demonstrate its capabilities of both active motion and passive compliance, which may improve adaptability in complex environments. Future work includes attachment of the spine to a quadruped robot to increase the overall workspace and generate rich motion skills. Full article

Gravity energy storage systems (GESS) have emerged as a promising long-duration energy storage technology capable of supporting large-scale renewable integration and enhancing grid resilience. However, the modeling framework for the hoisting electromechanical subsystem in wire-rope-based GESS remains underdeveloped, thereby limiting the accurate characterization of its transient grid-connected behavior, dynamic operating response, and cross-domain coupling effects. Existing studies commonly simplify wire ropes and related transmission components as rigid bodies or low-dimensional mechanical elements, failing to adequately account for their flexibility and the resulting high-dimensional nonlinear dynamics. Although related studies in mine hoisting and elevator systems have addressed mechanical vibration phenomena, they primarily focus on mechanical-side effects, such as shock loading and guide-structure response, whereas the mechanism by which flexible mechanical vibrations propagate through electromechanical coupling and influence electrical dynamic performance remains inadequately understood. To address this gap, this study establishes a distributed-parameter model for the wire-rope hoisting mechanism based on Hamilton’s principle and solves the corresponding vibration governing equations using the Galerkin method to capture nonlinear multi-modal dynamics. An electromechanical coupling model is then developed to elucidate how rope-vibration-induced tension fluctuations propagate through the drive chain, resulting in torque ripple, electrical interharmonics, and low-frequency grid-side oscillations. A Bessel-function-based analytical representation is further introduced to explain the formation of interharmonic clusters and beat-frequency phenomena under converter modulation. An experimental prototype is constructed to validate the proposed modeling framework. The measured vibration spectra, beat-frequency characteristics, and torque ripple align closely with analytical predictions, confirming the model’s capability to capture key propagation paths from rope vibration to electromechanical oscillation and grid-side dynamic response. The results provide a solid theoretical foundation for vibration mitigation, dynamic analysis, and control design of hoisting electromechanical subsystems in gravity energy storage applications. Full article

As extreme-scale manufacturing evolves, the dynamic response of heavy moving components under ultra-high loads becomes a critical design challenge. This study focuses on friction-induced vibration of a more than 30-ton movable mass during the mold-opening stage in a two-platen machine with a clamping force >17,000 kN. A mathematical model and a validated rigid/flexible multibody dynamics model with PID co-simulation were developed to analyze transient vibration using maximum acceleration amplitude and stability time as core metrics. The results show vibration stems from imbalance between anti-opening resistance and hydraulic driving force, amplified by vacuum collapse, static-to-dynamic friction transition at slide feet/rail interface and PID overshoot, featuring high amplitude density (>0.75 g), transience (<50 ms) and high impact (>60,000 N). The maximum vibration acceleration amplitude remains 79.22% even after there is no mold vacuum suction, indicating that a static friction force other than the vacuum suction is the dominant factor resulting in a severe friction-induced vibration. These mechanistic insights establish an applicable framework for the dynamic optimization of the heavy components in extreme-large-scale manufacturing equipment. Full article

The use of 3D printing in robotics enables lightweight, customized, and geometrically complex structures, but the resulting structural compliance challenges accurate dynamic prediction. Traditional rigid multibody models often neglect structural deformations and vibrations that can critically affect performance and control. This work presents initial advances toward a computational framework for flexible multibody dynamics of 3D-printed robotic structures. A two-link mechanism is modeled in MATLAB Simscape Multibody under both rigid and flexible assumptions, and parametric analyses are conducted to assess the influence of geometry, mass distribution, and stiffness on system dynamics. The proposed framework is formulated to accommodate reduced-order and data-driven modeling approaches for efficient simulation and analysis of flexible robotic mechanisms. Full article

The selective harvesting of leaves from flexible-stem crops remains a major challenge in agricultural mechanization due to stem compliance, heterogeneous petiole strength, and unstable tool–crop interaction. To address these issues, a bio-inspired ring-cutting and compliant clamping harvesting mechanism is proposed for low-damage selective harvesting under complex terrain conditions. Inspired by the adaptive attachment behavior of octopus suckers, a flexible compliant clamping interface combined with a ring-shaped sliding cutting structure was developed to stabilize flexible stems during harvesting. A coupled kinematic–force analytical model was established to characterize the interaction between tool motion, stem feeding, and cutting behavior. In addition, a sliding cutting mechanics model was introduced to analyze the relationship between cutting force and sliding angle. Dynamic multibody simulations were performed using ADAMS to verify the motion feasibility and trajectory stability of the proposed harvesting mechanism. Bench-scale experiments were conducted using mulberry branches as a representative flexible-stem crop, and a response surface methodology based on a Box–Behnken experimental design was applied to optimize key operational parameters. The optimal parameter combination included a chain linear speed of 0.18 m·s⁻¹, a feeding speed of 0.30 m·s⁻¹, and an installation angle of 36°. Under these conditions, the missed harvest rate was reduced to 9.2–9.8%, demonstrating improved harvesting stability compared with conventional rigid cutting mechanisms. The results indicate that integrating compliant stabilization with sliding cutting provides an effective engineering strategy for selective harvesting of flexible-stem crops in complex agricultural environments. Full article

Servo electric cylinders have been widely adopted in high-performance linear drive applications such as aerospace systems, robotic servo systems, medical equipment, advanced manufacturing, precision testing, and high-end equipment due to their advantages, including high cleanliness, compact structure, high transmission efficiency, and ease of achieving precise control. However, under complex operating conditions, system performance is influenced not only by control strategies but also closely related to factors such as friction, clearance, transmission flexibility, structural vibrations, and modeling accuracy. This paper reviews mainstream control strategies and dynamic simulation methods for servo electric cylinders, providing structured analysis and systematic evaluation of representative research. In terms of control strategies, key approaches, including classical PID control, robust nonlinear control, intelligent and learning-based control, and active disturbance rejection control, are discussed, with comparative analysis of their characteristics and limitations in tracking accuracy, robustness, adaptability, and engineering feasibility. Regarding dynamic modeling and simulation, methods such as multibody dynamics, finite element analysis, rigid-flexible coupling, and multi-domain collaborative simulation are reviewed, examining their applicability in nonlinear mechanism characterization, local structural response assessment, and high-fidelity system modeling. Current research indicates that servo cylinder control is evolving from single-method improvements toward integrated and composite approaches, while dynamic modeling has progressed from low-order simplified analyses to system-level, multi-level, and high-fidelity descriptions. Existing studies still face challenges, including insufficient unified evaluation criteria, inadequate cross-method comparisons, and insufficient integration between control design and high-fidelity models. Future research should focus on enhancing control-model co-design, experimental validation under complex conditions, and system-level optimization oriented toward intelligent and high-reliability systems. Full article

In flexible manufacturing systems, the composite mobile manipulator (CMM) is subject to nonlinear inertial disturbances arising from the dynamic coupling between the mobile platform and the robotic arm. These disturbances significantly impair positioning precision during grasping tasks. This paper addresses the dynamic decoupling of multi-body nonlinear inertial disturbances within CMM systems. Departing from the conventional “stop-then-plan” serial execution paradigm, we propose a full-cycle spatiotemporally coupled trajectory optimization method. The operation cycle is bifurcated into two synergistic stages: “dynamic calibration” and “static execution.” The dynamic calibration trajectory is pre-planned and executed synchronously during platform movement to actively compensate for inertial-induced pose deviations. Concurrently, the static execution trajectory is optimized and then triggered immediately upon platform standstill, ensuring a seamless and precise transition to the “Grasping Pose”. It is worth noting that the temporal characteristic central to this framework lies in the concurrent execution of static trajectory optimization and platform transit: by the time the platform reaches its destination, the pre-planned trajectory is already available for immediate triggering, achieving zero task-switching wait time at the planning layer. The term “zero-latency” here does not imply a fixed-cycle real-time response at the control layer, but rather the complete elimination of decision latency afforded by the parallel planning architecture. This framework eliminates computational latency, markedly enhancing operational efficiency. Key innovations include two novel constraints. First, the Adaptive Task-space Bounded Search Constraint (ATBSC) framework restricts optimization to a geometry-inspired search region, thereby enhancing search efficiency and ensuring controllable deviations. Second, the Multi-Rigid-Body Coupling Constraint (MRBCC) system explicitly models inertial transmission across motion phases to suppress pose fluctuations. The proposed framework is developed and validated within an obstacle-free workspace. In simulation-based validation on a UR10 6 degree-of-freedom manipulator model, experimental results indicate that ATBSC increases valid solution density to 84.7% and reduces average deviation by 72.8%. Furthermore, under the tested conditions, MRBCC mitigates end-effector position errors by 79.7–81.0% with a 97.5% constraint satisfaction rate. The improved Cuckoo Search algorithm (ICSA), serving as the solver component of the proposed framework, achieves an 11.9% lower fitness value and a 13.1% faster convergence rate compared to the standard Cuckoo Search algorithm in the tested scenarios, suggesting its effectiveness as a reliable solver for the constrained multi-objective trajectory optimisation problem. Full article

To address the vibration and noise issues induced by inertial forces in marine V-type air compressors during operation, this study systematically investigates inertial force balancing and optimization. Based on dynamic analysis, analytical expressions for the first- and second-order reciprocating inertial forces and the rotating inertial force under unbalanced conditions are precisely derived. Considering the characteristics of a V-type air compressor with a V-angle of γ = 60°, the synthesis model of the first-order reciprocating inertial force is modified. The positive–negative rotating wheel system method is employed for preliminary balancing design, and the rigid–flexible coupling dynamics theory is innovatively introduced to construct a high-precision multi-body dynamics model that accounts for the flexible deformation of the crankshaft and connecting rod. Through joint simulation using ANSYS (2024R1) and Adams (2024.2), the dynamic responses of the pure rigid-body model and the rigid–flexible coupling model are compared to determine the optimal balancing configuration. The Adams/Insight module is utilized to perform multi-objective optimization of the balance iron mass. Results indicate that the rigid–flexible coupling model more accurately reflects the dynamic characteristics of the air compressor compared to the pure rigid-body model, significantly enhancing simulation accuracy. The optimized balance iron configuration effectively suppresses system vibration, with the peak X-direction bearing reaction force decreasing from 3750 N to 3610 N (a reduction of 3.7%), the vibration intensity reducing by 45.3%, and the radiated noise sound power level decreasing by 7.45%. This study provides a systematic theoretical approach and technical pathway for vibration and noise reduction, as well as for structural reliability design of marine air compressors. Full article

This paper proposes a self-deployable pyramid truss based on water-drop buckling. By bending the straight beams of the pyramid truss into water-drop shapes, elastic potential energy is stored and released upon the removal of constraints, enabling the compressed structure to deploy rapidly and autonomously. Through multi-circle bending of the beam edges and multi-cell design of the pyramids, a higher folding ratio and larger structural size are achieved. Analytical calculations, numerical simulations, and physical experiments are conducted for both the water-drop buckling and pyramidal truss deployment. The comparison results demonstrate the correctness of the calculation method and the effectiveness of the self-deployable design. Full article

As a crucial initial step in humanity’s quest to explore deep space, lunar transfer missions have garnered significant attention. The escalating demand for increased payload capacity and mission flexibility have presented challenges in terms of mission fuel costs. In response, the design of low-energy lunar transfer trajectories, rooted in multibody dynamics, has become paramount for deep space exploration trajectory design. This paper summarizes the design methods for transfer trajectories from the Earth to the Moon and even deeper space that consume low energy at the expense of expanded transfer time. The fundamental design methods include the weak stability boundary method, the chaos control method, and the invariant manifold theory, which are primarily determined by dynamical mechanisms. Additionally, the paper discusses the low-thrust technique, formulating trajectory design as an optimization problem to tailor thrust profiles for minimum fuel consumption. Finally, landmark missions are discussed to demonstrate the practical applications and advantages of low-energy trajectories, spanning lunar missions to exploration within deeper space regions. Full article