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To investigate the multifield coupled vibration properties of electric-drive systems of electric vehicles, an improved equivalent magnetic network model of a permanent magnet synchronous motor suitable for variable speed/load and other non-stationary conditions is established by considering the nonlinear factors such as stator slotting, pole distribution, and magnetic saturation. On this basis, a machine-electric–magnetic multi-field coupling dynamics model of the electric drive system is established by comprehensively considering the gear transmission error, time-varying meshing stiffness, etc. The laws affecting the dynamic properties of the electric drive system under excitation of the internal nonlinear factors and external load are investigated. Research shows that electromagnetic excitation exacerbates the vibration amplitude of the gear. Mechanical excitation modulates the current frequency. The system vibration response amplitude trend is consistent with the current low-frequency harmonic components that can be used to monitor the system vibration state. External shock loads have the greatest impact on the vibration of the first-stage active gear and secondary-stage driven gear. The coupling effect of the motor and gear can effectively suppress the shock oscillation caused by a sudden change in the load. [ABSTRACT FROM AUTHOR]

In autonomous driving, accurately predicting the trajectories of surrounding vehicles is essential, particularly in dense and heterogeneous urban traffic. We propose a graph-structured model with a category layer to efficiently forecast the target vehicle’s trajectory. The model enables flexible selection of interacting objects based on environmental interactions and extracts spatial-temporal features using a graph convolutional network. A categorical layer is introduced to account for the different influences of dynamic agents, while vehicle dynamics constraints ensure the feasibility of predicted trajectories. We developed a new heterogeneous and dense urban unsignalized intersection dataset (HID), capturing complex urban interactions, and conducted extensive experiments on HID, ApolloScape, and TRAF datasets. Results demonstrate that our model outperforms benchmark methods across diverse urban scenarios, and the integration of key modules significantly enhances prediction accuracy and performance. [ABSTRACT FROM AUTHOR]

Weather survival poses a significant challenge for the utilization of tethered balloons. The dynamic modeling of tethered balloon systems presents challenges due to the flexible nature of the cables and the intricate nature of gust forces. The present study introduces a new approach for modeling near-ground tethered balloon systems, which enables the analysis of their dynamic responses and performance evaluation under complex boundary conditions. First, finite cylindrical rigid bodies that are joined together by bushing forces to describe the dynamics of the tethered cable. The properties of the flexible cables under severe bending and translation can be illustrated by the dynamics model. Second, a three-dimensional dynamics model based on the multibody dynamics theory is created to deal with the interaction of the tethered balloon system and flexible cables. The dynamic responses of the tethered balloon system under challenging operating conditions are investigated, focusing on the number of cable segments and the place and direction of gust wind impacts. This model allows for precise assessment and optimization of the system's overall performance to improve weather resistance. The results show that compared to computational fluid dynamics (CFDs) methods, the multibody system dynamics-based balloon model improved the solution time by 80%, with a pitch angle deviation of only 0.0016°. Moreover, the bushing model effectively reduced cable force and enabled accurate reflection of the system's motion characteristics. [ABSTRACT FROM AUTHOR]

A one-dimensional homogeneous reactor model was developed to simulate the dynamic behavior of a fixed-bed reactor for a catalytic coupling reactor of carbon monoxide and ethyl nitrite to diethyl oxalate. Reactor modeling was performed using a comprehensive numerical model that was simulated using Simulink. The power law kinetic model was applied for simulating the catalytic coupling reaction considering the main and side reactions. The heat of reaction was calculated with respect to the reacted moles of ethyl nitrite for each reaction. When the simulated model reached a steady state, the predicted results were in agreement with the actual data that was collected from an already established pilot plant fixed bed reactor. The startup dynamic behavior of hypothetical industrial-scale production of diethyl oxalate at 78,000 tons per year was simulated. The system reached steady-state within 14–16 min at a space velocity of 1400 h−1.

As an ingenious convergence between the Internet of Things and social networks, the Social Internet of Things (SIoT) can provide effective and intelligent information services and has become one of the main platforms for people to spread and share information. Nevertheless, SIoT is characterized by high openness and autonomy, multiple kinds of information can spread rapidly, freely and cooperatively in SIoT, which makes it challenging to accurately reveal the characteristics of the information diffusion process and effectively control its diffusion. To this end, with the aim of exploring multi-information cooperative diffusion processes in SIoT, we first develop a dynamics model for multi-information cooperative diffusion based on the system dynamics theory in this paper. Subsequently, the characteristics and laws of the dynamical evolution process of multi-information cooperative diffusion are theoretically investigated, and the diffusion trend is predicted. On this basis, to further control the multi-information cooperative diffusion process efficiently, we propose two control strategies for information diffusion with control objectives, develop an optimal control system for the multi-information cooperative diffusion process, and propose the corresponding optimal control method. The optimal solution distribution of the control strategy satisfying the control system constraints and the control budget constraints is solved using the optimal control theory. Finally, extensive simulation experiments based on real dataset from Twitter validate the correctness and effectiveness of the proposed model, strategy and method.

Cable-driven parallel robots (CDPRs) have been gaining much attention due to their many advantages over traditional parallel robots or serial robots, such as their markedly large workspace and lightweight design. However, one of the main issues that needs to be urgently solved is the tension in the distribution of CDPRs due to two reasons. The first is that a cable can only be stretched but not compressed, and the other is the redundancy of the parallel robot. To address the problem, an optimization method for tension distribution is proposed in the paper. The structural design of the parallel robot is first discussed. The dynamics model of the parallel robot is established by the Newton–Euler method. Based on the minimum variance of cables' tension, an optimization method of tension distribution is presented for the parallel robot. Furthermore, the tension extreme average term is introduced in the optimization method, and the firefly algorithm is applied to obtain the optimal solution for tension distribution. Finally, the proposed approach is tested in the simulation case where the end-effector of the robot moves in a circular motion. Simulation results demonstrate that the uniformity and continuity of tension are both outstanding for the proposed method. In contrast with traditional solving methods, the efficiency of this method is largely improved. [ABSTRACT FROM AUTHOR]

The rotating blade is a key component of an aero-engine, and its vibration characteristics have an important impact on the performance of the engine and are vital for condition monitoring. This paper reviews the research progress of blade dynamics, including three main aspects: modeling of blades, solution methods, and vibration characteristics. Firstly, three popular structural dynamics models for blades are reviewed, namely lumped-mass model, finite element model, and semi-analytical model. Then, the solution methods for the blade dynamics are comprehensively described. The advantages and limitations of these methods are summarized. In the third part, this review summarizes the properties of the modal and vibration responses of aero-engine blades and discusses the typical forms and mechanisms of blade vibration. Finally, the deficiencies and limitations in the current research on blade modeling and vibration analysis are summarized, and the directions for future efforts are pointed out. The purpose of this review is to provide meaningful insights to researchers and engineers in the field of aero-engine blade modeling and dynamic characteristics analysis. [ABSTRACT FROM AUTHOR]

A one-dimensional homogeneous reactor model was developed to simulate the dynamic behavior of a fixed-bed reactor for a catalytic coupling reactor of carbon monoxide and ethyl nitrite to diethyl oxalate. Reactor modeling was performed using a comprehensive numerical model that was simulated using Simulink. The power law kinetic model was applied for simulating the catalytic coupling reaction considering the main and side reactions. The heat of reaction was calculated with respect to the reacted moles of ethyl nitrite for each reaction. When the simulated model reached a steady state, the predicted results were in agreement with the actual data that was collected from an already established pilot plant fixed bed reactor. The startup dynamic behavior of hypothetical industrial-scale production of diethyl oxalate at 78,000 tons per year was simulated. The system reached steady-state within 14–16 min at a space velocity of 1400 h−1. [ABSTRACT FROM AUTHOR]

Accurately modeling the system dynamics of autonomous underwater vehicles (AUVs) is imperative to facilitating the implementation of intelligent control. In this research, we introduce a physics-informed neural network (PINN) method to model the dynamics of AUVs by integrating dynamical equations with deep neural networks. This integration leverages the nonlinear expressive power of deep neural networks, alongside the robust foundation of physical prior knowledge, resulting in an AUV model proficient in long-term motion forecasting. The experimental results indicate that this method is capable of effectively extracting AUV system dynamics from datasets, exhibiting strong generalization capabilities and achieving robust long-term motion prediction. Furthermore, a model predictive control method is proposed, using the learned PINN as the predictive model to accurately track the closed-loop trajectory. This research offers novel perspectives on the dynamics modeling of AUVs and has the potential to be applied in other relevant research endeavors. [ABSTRACT FROM AUTHOR]

The 1/6g environment simulation system is essential in scientific research, exploration, and future space development. The system is technically demanding and must accurately simulate a low-gravity environment while ensuring the reliability and precision of the experiment, which involves complex machinery and control systems that are technically challenging. This paper proposes a new simulation experiment method that combines the traditional hanging low-gravity simulation method and magnetic levitation technology.Realization of the design of the magnetic levitation suspended low gravity simulation system. The magnetically levitated overhead crane, which counteracts 5/6 of the lunar rover’s gravity, is the most important component of the entire test system. The article first designs the principle scheme of the magnetically levitated hanging active following a low gravity simulation system, which reduces the influence of the bulky wheel slip structure of the existing equipment on the experiment and improves the system’s anti-interference ability. Secondly, the article establishes the dynamics model of the magnetic suspension crane tracking system, analyzes and derives the relationship between the force, the magnetic suspension air gap and the voltage, and lays a theoretical foundation for the smooth operation of the precise control system. Finally, based on the cross-coupling control strategy, the magnetic suspension crane following control system is designed and the cross-coupling control system model is established.

Aiming at the rehabilitation training of patients with lower extremity damage and stroke, a multi-degree-of-freedom adjustable lower extremity rehabilitation exoskeleton is designed. The screw mechanism is used to replace the traditional leg structure, and there is a rotation module at the waist, which can better realize the human-machine collaboration. The lower extremity exoskeleton dynamics model is established by the Lagrangian method, and the theoretical torque is calculated; the lower extremity rehabilitation exoskeleton model is constructed, and the finite element simulation and exoskeleton kinematics/dynamics simulation are carried out using Ansys and Adams software, respectively. The results verify the rationality of the structural design, and provide a basis for the subsequent lower limb exoskeleton manufacturing and motor selection.

Weather survival poses a significant challenge for the utilization of tethered balloons. The dynamic modeling of tethered balloon systems presents challenges due to the flexible nature of the cables and the intricate nature of gust forces. The present study introduces a new approach for modeling near-ground tethered balloon systems, which enables the analysis of their dynamic responses and performance evaluation under complex boundary conditions. First, finite cylindrical rigid bodies that are joined together by bushing forces to describe the dynamics of the tethered cable. The properties of the flexible cables under severe bending and translation can be illustrated by the dynamics model. Second, a three-dimensional dynamics model based on the multibody dynamics theory is created to deal with the interaction of the tethered balloon system and flexible cables. The dynamic responses of the tethered balloon system under challenging operating conditions are investigated, focusing on the number of cable segments and the place and direction of gust wind impacts. This model allows for precise assessment and optimization of the system’s overall performance to improve weather resistance. The results show that compared to computational fluid dynamics (CFDs) methods, the multibody system dynamics-based balloon model improved the solution time by 80%, with a pitch angle deviation of only 0.0016°. Moreover, the bushing model effectively reduced cable force and enabled accurate reflection of the system’s motion characteristics.

Copyright of Acta Scientiarum Naturalium Universitatis Sunyatseni / Zhongshan Daxue Xuebao is the property of Sun-Yat-Sen University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The non-uniform load distribution of crowned roller along the contact line has a significant impact on the dynamic characteristics and fatigue life of the roller linear guideway workbench (RLGW). Moreover, the randomness in the design parameters due to unavoidable manufacturing errors will induce the uncertainty in the vibration prediction of RLGW, which will affect the machining accuracy of machine tool. To this end, this paper first establishes a novel five-DOF dynamic model considering the non-uniform load distribution of crowned roller to investigate the vibration characteristics of RLGW. The coordinate transformation method is used to obtain the vibrations at the four raceways of carriage by applying the workbench vibrations. The Hertz contact theory and the slicing method are applied to calculate the contact force and moment of crowned roller including the influence of roller profile, and a time-varying five-DOF restoring force model dependent on the workbench vibrations is established. Then, to improve the computing efficiency, a vibration reliability evaluation method of RLGW based on the active learning Kriging model and Monte Carlo Simulation (ALK-MCS) method is proposed. The developed dynamics modeling method is verified by some experiments on a CNC milling machine workbench system. The changes in the vibration characteristics and stiffness of RLGW are studied by varying the preload degree and number of loaded rollers. Furthermore, the vibration reliability and reliability sensitivity of RLGW are studied to provide theoretical foundation for the parameter optimization. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Vibration, Measurement & Diagnosis is the property of Nanjing Hangkong Daxue and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The rotating blade is a key component of an aero-engine, and its vibration characteristics have an important impact on the performance of the engine and are vital for condition monitoring. This paper reviews the research progress of blade dynamics, including three main aspects: modeling of blades, solution methods, and vibration characteristics. Firstly, three popular structural dynamics models for blades are reviewed, namely lumped-mass model, finite element model, and semi-analytical model. Then, the solution methods for the blade dynamics are comprehensively described. The advantages and limitations of these methods are summarized. In the third part, this review summarizes the properties of the modal and vibration responses of aero-engine blades and discusses the typical forms and mechanisms of blade vibration. Finally, the deficiencies and limitations in the current research on blade modeling and vibration analysis are summarized, and the directions for future efforts are pointed out. The purpose of this review is to provide meaningful insights to researchers and engineers in the field of aero-engine blade modeling and dynamic characteristics analysis.

Cable-driven parallel robots (CDPRs) have been gaining much attention due to their many advantages over traditional parallel robots or serial robots, such as their markedly large workspace and lightweight design. However, one of the main issues that needs to be urgently solved is the tension in the distribution of CDPRs due to two reasons. The first is that a cable can only be stretched but not compressed, and the other is the redundancy of the parallel robot. To address the problem, an optimization method for tension distribution is proposed in the paper. The structural design of the parallel robot is first discussed. The dynamics model of the parallel robot is established by the Newton–Euler method. Based on the minimum variance of cables’ tension, an optimization method of tension distribution is presented for the parallel robot. Furthermore, the tension extreme average term is introduced in the optimization method, and the firefly algorithm is applied to obtain the optimal solution for tension distribution. Finally, the proposed approach is tested in the simulation case where the end-effector of the robot moves in a circular motion. Simulation results demonstrate that the uniformity and continuity of tension are both outstanding for the proposed method. In contrast with traditional solving methods, the efficiency of this method is largely improved.

A folding wing vertical take-off and landing (VTOL) UAV is capable of transitioning between quadrotor and fixed-wing modes, but significant alterations occur in its dynamics model and maneuvering mode during the transformation process, thereby imposing greater demands on the adaptability of its control system. In this paper, a multi-level switching control scheme based on dynamic allocation is proposed for the deformation stage. Firstly, according to the physical characteristics of the wing folding mechanism, a dynamic model is established. The influence of the incoming flow on the rotors is considered, and the dynamic coupling characteristics in its transition process are analyzed. Secondly, by inverting the changes in rotor position and axial direction, a dynamic allocation algorithm for the rotors is designed. Then, the quadrotor controller and the fixed-wing controller are switched and mixed in multiple loops to form a multi-level switching control scheme. Finally, the simulation results show that the designed multi-level switching control scheme is effective and robust in forward and backward deformation processes, and its anti-interference ability is stronger compared with that of the control scheme without dynamic allocation.

Existing robot gait control methods have problems such as high gait energy consumption and difficulty in generating optimal gait strategies. This paper designs a robot gait automatic control system based on the X86 platform and robot sensor interface. The main board of the robot controller is designed based on CISC, which ensures high stability and anti-interference capabilities. The information provided by ultrasonic sensors and infrared sensors is used to adjust and execute the robot’s trajectory, action sequence, and gait. To extract the target in the gait image, the frame difference algorithm is employed, and the phase and amplitude factors are collected after the Radon and Fourier-Mellin transform to identify gait characteristics for robot gait recognition. The robot’s two-dimensional spatial dynamics model is constructed continuously, and its dynamics equations are derived. The residual fusion technique is used to combine image data with sensor data. A system for stabilizing gait control has been designed. The tracking error rate of the robot is not more than ±10% in general, and a variety of gait patterns can be used to cross the obstacles, which verifies the effectiveness of the designed system for realizing the gait control and performance of the robot.

As countries attach great importance to the ocean-going navigation capability of ships, the energy consumption of shipborne equipment has attracted much attention. Although energy consumption analysis is a guiding method to improve energy efficiency, it often ignores the dynamic characteristics of the system. However, the traditional dynamic analysis method hardly considers the energy consumption characteristics of the system. In this paper, a new type of electric-driven helicopter traction system is designed based on the ASIST system. Combined with power bond graph theory, a system dynamic modeling method that considers both dynamic and energy consumption characteristics is proposed, and simulation analysis is carried out. The results indicate that the designed traction system in this study displays high responsiveness, robust, steady-state characteristics, and superior energy efficiency. When it engages with helicopter-borne aircraft, it swiftly transitions to a stable state within 0.2 s while preserving an efficient speed tracking effect under substantial load force, and no significant fluctuations are detected in the motor rotation rate or the helicopter movement velocity. Moreover, it presents a high energy utilization rate, achieving an impressive energy utilization rate of 84% per single working cycle. Simultaneously, the proposed modeling methodology is validated as sound and effective, particularly apt for the dynamic and power consumption analysis of marine complex machinery systems, guiding the high-efficiency design of the transmission system. [ABSTRACT FROM AUTHOR]

Copyright of Frontiers of Information Technology & Electronic Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Exploiting dynamic spatial and temporal features of location information for robot modeling is of great importance in many real applications. It has gained increasing attention in the era of the Internet of Things (IoT). However, successful modeling and accurate localization for robot in indoor environment is still a challenge, where the environment factors are complex and unpredictable, such as signal noise, obstacles and spare fingerprints. Existing studies usually employ data driven and learning based models to capture spatial and temporal features for robot location estimation, modeling dynamics of robot and make robot decision. However, the modeling and localization performance is not satisfied. In this paper, to address above challenges, a novel deep learning framework called multi-faceted deep learning based dynamics modeling and robot localization learning (DMLoc) method is proposed. Specifically, a localization attention module is designed to capture the features from original fingerprints and optimized fingerprints information. Then, a multi-faceted localization module is proposed, which integrates extraction model and optimized model with long short-term memory (LSTM) and gate recurrent unit (GRU). Moreover, a multi-feature fusion layer is designed to fuse the extracted features and generate localization results. Extensive simulation results show the efficiency of the proposed DMLoc. [ABSTRACT FROM AUTHOR]

In vehicle dynamics research, a dynamics model is essential, as it provides the basis for the demonstration of early system design of vehicle as well as the verification and optimization of the dynamics performance of the final product. To promote the development of a permanent magnet (PM) Electrodynamic Suspension (EDS) in a maglev train, research was carried out in order to explore a fast dynamics modeling, with suspension system based on two-sided PM. First of all, a halbach array was taken as the object of study, with the analytical solution of its magnetic force obtained by theoretical derivation according to magnet filed and 2D analytical method; then, the magnetic force was discretized into a data matrix of displacement, force, and speed; thirdly, the data matrix was introduced in SIMPACK to establish a magnet-track relationship in scalar form, and a dynamics model of the two-sided PM EDS maglev system was finished by the theory of multi-body dynamics modeling; finally, the proposed modeling was validated by the agreement between theoretical derivation and dynamics model calculation of the heaving frequency and pitching frequency of the frame; at the same time, it was also validated by the agreement of dynamic responses between the modeling by vehicle-track coupled dynamics theory and the dynamic model calculation of the levitation gap and force. According to the established dynamics model, dynamic response of the system at the speed of 600 km/h was calculated, and the feasibility of the two-sided PM EDS maglev train was verified. The simulation speed of model which was established before is 50 times that of the mathematical model by the vehicle-track coupled dynamics, thus providing reference for the future research in this regard. [ABSTRACT FROM AUTHOR]

The cable-driven parallel robot is a special flexible mechanism in parallel mechanism, the end-effector of which is driven by cables instead of rigid rods. It integrates the advantages of flexible robots and parallel robots. A three-degree-of-freedom (3-DOF) under-constrained parallel robot with variable cable mast heights is investigated in this study. The inverse kinematics model of the robot is established by using the vector closed-loop principle. The forward kinematics model of the robot is derived according to cable lengths. The dynamics model of the robot is established based on the Lagrange formula. The static equilibrium workspace (SEW) of the robot is studied using the Monte-Carlo method. Given the motion trajectory of the end-effector, the expected three cable lengths are obtained through the inverse kinematics model of the robot. Taking the expected three cable lengths as the experimental input, the experimental curves of cable lengths and cable tensions as well as the forward kinematics trajectory of the robot are obtained. The experimental results validate the correctness of the forward and inverse kinematics models and the dynamics model of the robot, as well as the effectiveness of the SEW.

Accurately modeling the system dynamics of autonomous underwater vehicles (AUVs) is imperative to facilitating the implementation of intelligent control. In this research, we introduce a physics-informed neural network (PINN) method to model the dynamics of AUVs by integrating dynamical equations with deep neural networks. This integration leverages the nonlinear expressive power of deep neural networks, alongside the robust foundation of physical prior knowledge, resulting in an AUV model proficient in long-term motion forecasting. The experimental results indicate that this method is capable of effectively extracting AUV system dynamics from datasets, exhibiting strong generalization capabilities and achieving robust long-term motion prediction. Furthermore, a model predictive control method is proposed, using the learned PINN as the predictive model to accurately track the closed-loop trajectory. This research offers novel perspectives on the dynamics modeling of AUVs and has the potential to be applied in other relevant research endeavors.

Since bioparticles experience large deformations, it is imperative to develop an appropriate model for particle modeling based on its size to prevent Nano biological particle destruction such as Bacillus, which is modeled as a Nano-beam. In this paper, models with large deformation assumptions were suggested for a longitudinal particle that can be geometrically considered as a beam. By modeling a nano/microparticle using continuum mechanics theory and dynamic simulation based on FEM, the dynamic behavior and shape deformation caused by the manipulation forces were examined. Hence, the manipulation of bioparticles with a cylindrical shape, named Bacillus Subtilis, was investigated. Critical time and forces and the predominant mode of movement of biological nanoparticles in a manipulation process were obtained and the Euler–Bernoulli theory was utilized to investigate the dynamic of biological nanoparticles. After the discretization of governing equations of motion using the Galerkin method, mass and stiffness matrices were extracted and critical forces were calculated to examine the dynamic behavior of particles. The effect of the aspect ratio showed that the deformation of the particle increases with increasing aspect ratio. In addition, the manipulation force is an essential parameter when small and large deflection models are compared. It was evident that the difference between linear and nonlinear deflection models at L/D = 100 was decreased from 39.47% for the 10 µN force to 12.46% for the 5 µN force. It was deduced that the small and large deflection models tend to have similar results with reducing force. [ABSTRACT FROM AUTHOR]

Most aircraft launchers exhibit a rapid acceleration of the launching aircraft, often exceeding ten times the acceleration due to gravity. However, only magnetic launchers offer flexible control over the propulsion force of the launcher cart, enabling precise control over the aircraft's acceleration and speed during its movement on the launcher. Consequently, extensive research is being conducted on magnetic launchers to ensure the repeatability of launch parameters, protect against aircraft overloads, and ensure operator safety. This article describes the process of modeling and analyzing the dynamical properties of a launch cart of an innovative prototype launcher, which employs a passive magnetic suspension with high-temperature superconductors, developed under the GABRIEL project. The developed mathematical model of the magnetic catapult cart was employed to conduct numerical studies of the longitudinal and lateral movement of the cart, as well as the configuration of the UAV–cart system during UAV takeoff under variable atmospheric conditions. An essential aspect of the research involved experimentally determining the magnetic levitation force generated by the superconductors as a function of the gap. The results obtained demonstrate that the analyzed catapult design enables safe UAV takeoff. External factors and potential vibrations resulting from uneven mass distribution in the UAV–cart system are effectively balanced by the magnetic forces arising from the Meissner effect and the flux pinning phenomenon. The primary advantage of the magnetic levitation catapult, in comparison to commercial catapults, lies in its ability to provide a reduced and consistent acceleration throughout the entire takeoff process. [ABSTRACT FROM AUTHOR]

Stability prediction of the securing system for autonomous trucks is an important prerequisite for achieving safety monitoring of large cargo transportation and improving logistics efficiency. Considering the side slide risk of large cargo and the inability to predict stability using the existing under-constrained friction securing model, this paper proposes a new vehicle–cargo securing model based on the 6-SPS parallel mechanism. By establishing an analytical 3-DOF model, the dynamics performance of the vehicle–cargo system is analyzed based on the response solution under sinusoidal excitations. To verify the correctness of the analytical model, a multi-body dynamics model of the whole vehicle–cargo system based on the three-dimensional geometric model and the 6-SPS parallel mechanism is established for simulation in ADAMS. According to road class, pavement roughness is modeled by a white noise power spectrum method as the excitation in the simulation. The results show that the dynamics response of the analytical model accords well with that of the simulation model, with relative errors of 8.34% and 0.036% in amplitude and frequency, respectively. The proposed method can provide theoretical support for accurate stability prediction and for achieving safety monitoring of large cargo transportation for autonomous trucks. [ABSTRACT FROM AUTHOR]

The train dynamics modeling problem is a challenging task due to the complex dynamic characteristics and complicated operating environment. The flexible formations, the heavy carriage load, and the nonlinear feature of air braking further increase the difficulty of modeling the dynamics of heavy haul trains. In this study, a novel data-driven train dynamics modeling method is designed by combining the attention mechanism (AM) with the gated recursive unit (GRU) neural network. The proposed learning network consists of the coding, decoding, attention, and context layers to capture the relationship between the train states with the control command, the line condition, and other influencing factors. To solve the data insufficiency problem for new types of heavy haul trains to be deployed, the model agnostic meta-learning (MAML) framework is adopted to achieve knowledge transferring from tasks supported by large amounts of field data to data-insufficient tasks. Effective knowledge transfer can enhance the efficiency of data resource utilization, reduce data requirements, and lower computational costs, demonstrating considerable potential in the application of sustainable development. The simulation results validate the effectiveness of the proposed MAML-based method in enhancing accuracy. [ABSTRACT FROM AUTHOR]

Due to the coupling effect of gears, the vibration of each rotor in the gear rotor bearing system is coupled and affected by each other. The study of the dynamics of the gear rotor bearing system must be analyzed based on a systematic and holistic concept. Therefore, the dynamic modeling and model reduction of the gear rotor bearing coupling system have always been a common concern. Based on the basic principle of gear meshing, this study establishes the geometric coupling model (or called kinematic coupling model) of the spur gear pair, helical gear pair, spur bevel gear pair and spiral bevel gear pair; and by using the transformation matrix of the coupling model, a unified, convenient and normative modeling method for the dynamic study of arbitrary complex gear-rotor-bearing coupled system including the above four kinds of gear pairs is given, which provides convenience for the dynamic study of complex gear shafting.

Considering the hysteresis effect of the harmonic reducer in the joint and that when the joint is subject to alternating load torques, the hysteresis effect will have great influence on the output precision. However, the load on each joint of the multi-DOF manipulator is not constant and the hysteresis effect of harmonic reducers in the joint should be considered when analyzing the precision of the manipulator's end motion. A stiffness model with the hysteresis effect is proposed. Combined with the Stribeck friction model, a dynamic model of the manipulator is established. By solving the model, the end motion trajectory of the manipulator considering the hysteresis of the harmonic reducer's torsional angle is obtained. The motion accuracy index is established and the influence of the hysteresis angle and torsional stiffness of harmonic reducers on the trajectory accuracy of manipulators is analyzed. The results can provide reference for the harmonic reducer in the engineering design process of manipulators.

With the wide application of intelligent and network technologies in the transportation industry, intelligent driving of mine truck has become an inevitable trend in the development of mining industry. Simulation test is one of the important means to accelerate the development and implementation of intelligent driving technology. Different from the intelligent single-vehicle solution of passenger car autonomous driving, the intelligent mining truck system takes the ground management and supervision system as the center for comprehensive dispatch and command, and the mining environment is complex and time-varying, which brings great challenges to the safe operation of intelligent driving of mine truck. Therefore, according to the characteristics of multi-vehicle collaborative control and complex and changeable environment of mine trucks, this paper builds a set of mine trucks intelligent multi-vehicle collaborative simulation platform that includes ground management and supervision system, vehicle intelligent driving computing platform, mining scene model, vehicle sensor model, and multi-vehicle collaborative simulation communication interface. This simulation platform has been successfully applied to the testing of on-board decision control algorithms and ground dispatch planning algorithms for a mining truck intelligent driving project, and can provide test support for the research and development of multi-vehicle intelligent technology.

High-bandwidth nano-positioning stages (NPSs) have boosted the advancement of modern ultra-precise, ultra-fast measurement and manufacturing technologies owing to their fast dynamic response, high stiffness and nanoscale resolution. However, the nonlinear actuation, lightly damped resonance and multi-axis cross-coupling effect bring significant challenges to the design, modeling and control of high-bandwidth NPSs. Consequently, numerous advanced works have been reported over the past decades to address these challenges. Here, this article provides a comprehensive review of high-bandwidth NPSs, which covers four representative aspects including mechanical design, system modeling, parameters optimization and high-bandwidth motion control. Besides, representative high-bandwidth NPSs applied to atomic force microscope and fast tool servo are highlighted. By providing an extensive overview of the design procedure for high-bandwidth NPSs, this review aims to offer a systemic solution for achieving operation with high speed, high accuracy and high resolution. Furthermore, remaining difficulties along with future developments in this fields are concluded and discussed.

The underwater glider has difficulty accessing the complex and narrow hadal trench for observation, which is affected by its limited regulation capability of pitch angle (−45°~45°). In this study, a compact attitude regulating mechanism is proposed to extend the regulation range of pitch angle from −90°to 90° and to install it on the hadal-class underwater glider Petrel-XPLUS. Subsequently, the dynamics model of Petrel-XPLUS is established using dual quaternions to solve the "gimbal lock" problem caused by the increased pitch angle range. Within the extended pitch range, the motion modes of the glider are enriched into long-range, virtual mooring, and Lagrangian float modes for long-range, small-area, and current-following observation missions, respectively, and are analyzed using the established dynamics model. Moreover, a ballast method was used to modify the pitch angle range and initial equilibrium state of a constructed underwater glider. Finally, Petrel-XPLUS achieved a pitch angle regulation range of −90°~90° in a water pool experiment and completed three consecutive profiles in a sea trial in the Challenger Deep, Mariana Trench, with all depths over 10,000 m, of which the maximum depth was 10,619 m. The proposed mechanism and methods can also be applied to other submersibles to facilitate ocean observations. [ABSTRACT FROM AUTHOR]

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Morphing aircraft have extremely important application prospects in aviation，aerospace，weapons and other fields. The smart morphing and flight control technology is a comprehensive technology that includes multiple disciplines and applications. In this paper，the specific classification and characteristics of the morphing aircraft are summarized. The development status of the morphing aircraft’s deformable structure and intelligent materials is analyzed. The dynamics modeling and flight control technology of the morphing aircraft are studied. The application status of the deformation technology in the fields of micro air vehicles， unmanned aerial vehicles，hypersonic aircraft and missiles is summarized. Finally，the key technologies that need to be broken through urgently，such as global highly bionic and high⁃speed cross localization，structure and control coupling influence mechanism，intelligent materials and variant structure and drive integration， are identified. [ABSTRACT FROM AUTHOR]

The dynamics model for coaxial lifting rotors can be used to study the controller design and flight simulation for coaxial-rotor aerial vehicles. However, both the computational efficiency and the accuracy should be considered. First, the computational model of the induced velocity of lifting rotor everywhere including the wake region is derived based on adjoint theorem. Then, the finite state dynamics model for coaxial lifting rotors with wake skew considered is developed by extending the finite state inflow model for single rotor. Finally, the equations for calculating the thrust of coaxial lifting rotors in the hover condition are given, and the test is conducted. The results show that the computational complexity of the proposed dynamics model for coaxial lifting rotors is acceptable, and the computational thrusts are almost close to the test results when the rotational speed is within a certain range, which can also reflect the trend of the thrust lost for coaxial lifting rotors.

The underwater glider, which relies on buoyancy and attitude adjustments to achieve spatial motion, is an energy-saving observation platform for ocean phenomenon. Accurate dynamic models have important guiding significance for performance evaluation and controller design of the glider. This paper takes the Petrel glider as the research object, and establishes four types of dynamic models considering different ranges of attack angle, which has never been reported before. The model difference is mainly reflected in the viscous hydrodynamic equations obtained by using polynomials to fit computational fluid dynamics (CFD) simulation results. Then, some numerical cases are given to study the dynamics response difference of these models considering the ideal working condition and complex water current environments, respectively. The results indicate that there is not obvious dynamics response difference under the steady-state gliding condition, and the difference mainly occurs during the glider motion transition stage. Under the complex water current conditions, the dynamics response difference will be very significant, and the traditional dynamic models may exhibit the non-convergence issues. The comprehensive model established in this paper, which fully considers the ranges of attack angle, can better simulate the dynamics behavior of the glider and can provide certain theoretical guidance for actual application. • Four types of dynamic models of underwater gliders considering different ranges of attack angle. • Comparative study of these models considering ideal working condition and complex water current environments. • The comprehensive model of the glider, which fully considers the ranges of attack angle, is proposed. [ABSTRACT FROM AUTHOR]

Deep reinforcement learning (DRL) has shown remarkable capabilities in solving sequential decision-making problems. However, DRL requires extensive interactions with image-based environments. Existing methods have combined self-supervised learning or data augmentation to improve sample efficiency. While understanding the temporal information dynamics of the environment is important for effective learning, many methods do not consider these factors. To address the sample efficiency problem, we propose dynamics modeling with sequential temporal information (DynaSTI) that incorporates environmental dynamics and leverages the correlation among trajectories to improve sample efficiency. DynaSTI uses an effective learning strategy for state representation as an auxiliary task, using gated recurrent units to capture temporal information. It also integrates forward and inverse dynamics modeling in a hierarchical configuration, enhancing the learning of environmental dynamics compared to using each model separately. The hierarchical structure of DynaSTI enhances the stability of inverse dynamics modeling during training by using inputs derived from forward dynamics modeling, which focuses on feature extraction related to controllable state. This approach effectively filters out noisy information. Consequently, using denoised inputs from forward dynamics modeling results in improved stability when training inverse dynamics modeling, rather than using inputs directly from the encoder. We demonstrate the effectiveness of DynaSTI through experiments on the Atari game benchmark, limiting the environment interactions to 100k steps. Our extensive experiments confirm that DynaSTI significantly improves the sample efficiency of DRL, outperforming comparison methods in terms of statistically reliable metrics and nearing human-level performance. [ABSTRACT FROM AUTHOR]