Search Results (548)

Multi-axle vehicles are commonly used for heavy-duty special operations, which easily leads to high driving torque demands when adopting distributed electric drive configurations. This study achieves the objective of reducing the driving torque of each in-wheel motor while controlling the stability of multi-axle vehicles. Taking a five-axle distributed drive test vehicle as the research object, a hierarchical control strategy integrating active all-wheel steering and direct yaw moment control is proposed. The upper layer is implemented based on model predictive control, with fuzzy control introduced to dynamically adjust control weights; the lower layer accomplishes the allocation of targets calculated by the upper layer through minimizing the objective function of tire load ratio. A linear parameter varying (LPV) tire model is introduced into the vehicle model to improve the calculation accuracy of tire lateral forces, and a neural network method is employed to solve the real-time performance issue of the model predictive control (MPC) controller. The proposed strategy is verified through a combination of simulation and real vehicle tests. High-speed condition simulations demonstrate that the AWS/DYC strategy significantly outperforms the ARS/DYC approach: compared to the active rear-wheel steering strategy, while the sideslip angle is reduced by 90.98%, the peak driving torque is reduced by 30.78%. Notably, tire slip angle analysis reveals that AWS/DYC maintains relatively uniform slip angle distribution across axles with a maximum of 4.7°, entirely within the linear working region, optimally balancing tire performance utilization with lateral stability while preserving safety margin, whereas ARS/DYC causes slip angles to exceed 11.9° at the rear axle, entering saturation. Low-speed real vehicle tests further confirm the engineering applicability of the strategy. The proposed method is of significant importance for the application of distributed drive configurations in the field of special vehicles. Full article

Recently, unmanned aerial vehicles (UAVs) based on electric propulsion systems are being increasingly adopted in various fields, including industrial and military applications. Outer-rotor surface-mounted permanent magnet synchronous motors (SPMSMs) are predominantly applied in UAV propulsion systems. However, these motors are vulnerable to the price fluctuations of rare-earth materials and supply chain instability. In addition, the magnets in these motors are prone to detachment at high rotational speeds, and demagnetization under high-temperature conditions may reduce output performance. To address these limitations, research is being actively conducted on non-permanent magnet motors, among which, wound-rotor synchronous motors (WRSMs) offer the advantage of controllable field excitation at high speeds. Furthermore, WRSMs can use both magnetic and reluctance torques, thereby increasing power density relative to other non-permanent magnet motors. However, the adoption of an additional field winding increases copper loss, thus reducing motor efficiency. This study investigates the application of the toroidal winding structure, which is already widely applied in permanent magnet and brushless direct current machines, to WRSMs. The performance of these motors is compared with that of motors using conventional tooth-coil windings. The toroidal windings are circumferentially distributed along both the inner and outer stator yoke paths, effectively reducing the end-turn length relative to that of conventional tooth-coil windings. Two WRSMs, one with tooth-coil and another with toroidal windings, are designed using identical specifications to compare performances via finite element analysis. The armature copper loss in the proposed model decreased by approximately 28% because the toroidal winding structure reduced the end-turn length. As a result, the efficiency increased by about 1.9% due to the reductions in copper, core, and eddy current losses. Full article

Distributed drive electric vehicles (DDEVs) offer remarkable advantages in handling stability owing to the independent torque and steering control of each wheel. Traditional in-dependent strategies have the disadvantages of slow response speed and unsmooth control interval switching. To overcome the performance tradeoffs of traditional independent strategies, this study proposes an integrated control approach combining four-wheel steering (4WS) and direct yaw moment control (DYC) to achieve coordinated multiobjective optimization. Based on phase-plane theory, the vehicle’s stable domain is divided using a double line method, and speed-dependent control regions and weights are designed to enable smooth switching between control modes. Simulation results demonstrate that, in high-adhesion conditions, compared with the DYC-only strategy, the integrated system reduces the maximum sideslip angle by about 77.8% and the cost function peak by 22.4%. Moreover, it decreases the maximum rear-wheel steering angle by 38.4% and maximum sideslip angle by about 15.4% compared with 4WS-only strategy. Under low-adhesion conditions, compared with the DYC-only strategy, the integrated system reduces the maximum sideslip angle by about 21.1% and the cost function peak by 37.6%. Additionally, the integrated system decreases the maximum rear-wheel steering angle by 60.2% and maximum sideslip angle by about 64.3% compared with 4WS-only strategy. Full article

In recognising both the emerging industrial applications of multi-link robotic manipulators and the inherent challenges of modelling and controlling their highly complex nonlinear dynamics, this work proposes a completely model-free terminal sliding mode control (MFTSMC) design approach to reduce the sensitivity and complexity often associated with model-based routines. Consequently, the proposed design achieves strong robustness, simplicity, and good operation tuning by eliminating the need for system modelling and enabling direct operator–machine interaction. Simulink simulations on a 3-link case subjected to different disturbance conditions (free, low-frequency, high-frequency, and mixed) show rapid dynamic convergence, good tracking precision, and strong disturbance rejection. The system reaches the sliding surface within 0.07 s, maintains steady-state errors around ${10}^{-2}$, and achieves a smooth torque response with low energy costs. The benchmark results confirm the finite-time convergence and demonstrate that the proposed framework is practical and scalable for multi-DOF systems and has potential for underactuated manipulators. It should be noted that a generalised dynamic model for a planar n-link manipulator is presented in the study for (1) the ground truth of the manipulator in simulation (not for the MFTSMC design), (2) the model-based controller designs in comparison to the MFTSMC, and (3) understanding the dynamic characteristics. Full article

This paper proposes an event-triggered extension of duty-ratio-based model predictive direct speed control (DR-MPDSC) for permanent magnet synchronous motor (PMSM) drives in electric vehicle (EV) applications. The main contribution is the development of an event-triggered execution framework specifically tailored to DR-MPDSC, in which control updates are performed only when the speed tracking error violates a prescribed condition, rather than at every sampling instant. Unlike conventional MPDSC and time-triggered DR-MPDSC schemes, the proposed strategy achieves a significant reduction in control execution frequency while preserving fast dynamic response and closed-loop stability. An optimized duty-ratio formulation is employed to regulate the effective application duration of the selected voltage vector within each sampling interval, resulting in reduced electromagnetic torque ripple and improved stator current quality. An extended Kalman filter (EKF) is integrated to estimate rotor speed and load torque, enabling disturbance-aware predictive speed control without mechanical torque sensing. Furthermore, a unified field-weakening strategy is incorporated to ensure wide-speed-range operation under constant power constraints, which is essential for EV traction systems. Simulation and experimental results demonstrate that the proposed event-triggered DR-MPDSC achieves steady-state speed errors below 0.5%, limits electromagnetic torque ripple to approximately 2.5%, and reduces stator current total harmonic distortion (THD) to 3.84%, compared with 5.8% obtained using conventional MPDSC. Moreover, the event-triggered mechanism reduces control update executions by up to 87.73% without degrading transient performance or field-weakening capability. These results confirm the effectiveness and practical viability of the proposed control strategy for high-performance PMSM drives in EV applications. Full article

This study investigated the effects of 6 weeks of plyometric training (PT) performed on soft (unstable) and hard (stable) surfaces compared with conventional training on the balance, explosive power, and muscle strength of adolescent female basketball players. The participants were randomly assigned to three groups: soft-surface PT (n = 14), hard-surface PT (n = 14), and conventional training (n = 14). Performance outcomes included 30 m sprint time, vertical jump height, plantar flexion and dorsiflexion maximal voluntary isometric contraction (MVIC) torque, Y-balance dynamic balance, and center of pressure-based static balance. Ground reaction forces, MVIC torques, and balance parameters were measured using high-precision force sensors to ensure accurate quantification of biomechanical performance. Statistical analyses were performed using two-way repeated-measures ANOVA with post hoc comparisons to evaluate group × time interaction effects across all outcome variables. Results demonstrated that soft- and hard-surface PT significantly improved sprint performance, vertical jump height, and plantar flexion MVIC torque compared with conventional training, while dorsiflexion MVIC increased similarly across all the groups. Notably, soft-surface training elicited greater enhancements in vertical jump height, dynamic balance (posteromedial and posterolateral directions), and static balance under single- and double-leg eyes-closed conditions. The findings suggest that PT on an unstable surface provides unique advantages in optimizing neuromuscular control and postural stability beyond those achieved with stable-surface or conventional training. Thus, soft-surface PT may serve as an effective adjunct to traditional conditioning programs, enhancing sport-specific explosive power and balance. These results provide practical guidance for designing evidence-based and individualized training interventions to improve performance and reduce injury risk among adolescent female basketball athletes. Full article

This review addresses the pivotal challenge in distributed-drive electric vehicle (DDEV) dynamics control: how to optimally distribute braking and steering forces during combined maneuvers to simultaneously enhance lateral stability, safety, and energy efficiency. The over-actuated nature of DDEVs presents a unique opportunity for precise torque vectoring but also introduces complex coupled dynamics, making vehicles prone to instability such as rollover during aggressive steering–braking scenarios. Moving beyond a simple catalog of methods, this work provides a structured synthesis and evolutionary analysis of chassis control methodologies. The problem is first deconstructed into two core control objectives: lateral stability and longitudinal braking performance. This is followed by a critical analysis of how integrated control architectures resolve the inherent conflicts between them. The analysis reveals a clear trajectory from independent control loops to intelligent, context-aware coordination. It further identifies a paradigm shift from the conventional goal of merely maintaining stability toward proactively managing stability boundaries to enhance system resilience. Furthermore, this review highlights the growing integration with high-level motion planning in automated driving. By synthesizing the current knowledge and mapping future directions toward deeply integrated, intelligent control systems, it serves as both a reference for researchers and a design guide for engineers aiming to unlock the full potential of the distributed drive paradigm. Full article

For long horizontal-section drilling in reservoirs and complex formations, efficient and robust trajectory planning with real-time closed-loop control must be achieved under curvature and mechanical constraints. This study systematically investigates the application of the Dubins curve, a shortest-path model satisfying a minimum curvature constraint, in closed-loop wellbore trajectory control. Six canonical configurations (LSL, RSR, LSR, RSL, LRL, and RLR) are analyzed, and a standardized procedure for path solution and coordinate reconstruction is established. Parametric analyses reveal the effects of curvature limit, target direction, and target distance on trajectory feasibility and path length. Case studies show that unoptimized Dubins trajectories can achieve a high reservoir-contact ratio (99.69%) but exhibit curvature discontinuities at segment junctions, which induce torque and friction peaks. By introducing a multi-objective optimization strategy combining minimum turning-radius expansion and adaptive target adjustment, these curvature discontinuities are effectively mitigated: the maximum curvature was reduced to 11.15°/30 m, the average curvature to 2.57°/30 m, the average friction to 1118.7 N, and the cumulative torque to 31,468 Nm, while maintaining nearly unchanged reservoir contact. The proposed method effectively improves trajectory smoothness and mechanical drillability while preserving real-time computational efficiency, offering a practical approach for closed-loop trajectory optimization in complex geological settings. Full article

Accurately estimating the absolute position of robots under external loads is challenging due to nonlinear dynamics, posture-dependent manipulability, and structural sensitivities. This study investigates a data-driven approach for absolute position prediction of a 2-DOF planar delta robot by learning time-series force signals generated during manipulability-driven free motion. Constant torques of opposite directions were applied to the robot without any position or trajectory control, allowing the mechanism to move naturally according to its configuration-dependent manipulability. Reaction forces measured at the end-effector and relative encoder variations were collected across a grid of workspace locations and used to construct a 12-channel time-series input. A hybrid deep learning architecture combining 1D convolutional layers and a bidirectional LSTM network was trained to regress the robot’s absolute X–Y position. Experimental results demonstrate that the predicted trajectories closely match the measured paths in the workspace, yielding overall RMSE values of 3.81 mm(X) and 2.94 mm(Y). Statistical evaluation using RMSE shows that approximately 83.73% of all test sequences achieve an error below 5 mm. The findings confirm that LSTM models can effectively learn posture-dependent dynamic behavior and force-manipulability relationships. Full article

Background: Robotic assistive devices are increasingly used in post-stroke gait rehabilitation, yet quantitative evaluations of synchronization between human and robotic joint motion remain limited. This study examined gait kinematics in post-stroke hemiplegic patients using two exoskeleton-type devices—HAL^® (Cyberdine Inc., Tsukuba, Japan) and curara^® (AssistMotion Inc., Ueda, Japan)—based on synchronized IMU measurements. Methods: Two post-stroke patients performed treadmill walking under non-assisted and assisted conditions with HAL^® and curara^®. Only the paretic knee joint was analyzed to focus on the primary control joint during gait. Inertial measurement units (IMUs) simultaneously recorded human and robotic joint angles. Synchronization was assessed using Bland–Altman (BA) analysis, root mean square error (RMSE), and mean synchronization jerk (MSJ). The study was designed as an exploratory methodological case study to verify the feasibility of synchronized IMU-based human–robot joint measurement. Results: Both assistive devices improved paretic knee motion during gait. RMSE decreased from 7.8° to 4.6° in patient A and from 8.1° to 5.0° in patient B. MSJ was lower during curara-assisted gait than HAL-assisted gait, indicating smoother temporal coordination. BA plots revealed reduced bias and narrower limits of agreement in assisted conditions, particularly for curara^®. Differences between HAL^® and curara^® reflected their distinct control strategies—voluntary EMG-based assist vs. cooperative gait-synchronization—rather than superiority of one device. Conclusions: Both devices enhanced synchronization and smoothness of paretic knee motion. curara^® demonstrated particularly smooth torque control and consistent alignment with human movement. IMU-based analysis proved effective for quantifying human–robot synchronization and offers a practical framework for optimizing robotic gait rehabilitation. The novelty of this study lies in the direct IMU-based comparison of human and robotic knee joint motion under two contrasting assistive control strategies. Full article

The Space Solar Power Station/Satellite (SSPS) is a large-scale space-borne facility intended for the direct collection and conversion of solar energy in the extra-stratospheric region. The optimization of its light collection and conversion (LCC) structures, analysis of dynamic characteristics, and design of attitude control systems represent core technical bottlenecks impeding the advancement of SSPS. To address these issues, this study investigates a novel conceptual line-focusing SSPS. Firstly, a multi-objective collaborative optimization model is developed to optimize the structural parameters of the concentrator and photovoltaic (PV) array. Subsequently, based on the optimized parameters, a coupled multi-body dynamic model is formulated, incorporating gravity-gradient torque and other space-borne disturbance factors. Finally, a distributed Proportional–Integral–Derivative (PID) controller is proposed to achieve three-axis attitude stabilization of the SSPS. Simulation results demonstrate that the light collection efficiency achieves 81.9% with a power density of 4792.24 W/m²; concurrently, a balance between the geometric parameters of the LCC system and the aforementioned key performance indicators is attained, and the proposed controller possesses favorable anti-disturbance performance. Full article

When operating in the marine environment, floating offshore wind turbines (FOWTs) are subjected to various inflow conditions such as wind, waves, and currents. To investigate the effects of complex inflow conditions on offshore wind farms, an integrated fluid-structure interaction computational and coupled dynamic analysis method for FOWTs is employed. An aero-hydro-servo-elastic coupled analysis model of the NREL 5 MW semi-submersible wind turbine array based on the OC4-DeepCwind platform is established. The study examines the variations in power generation, platform motion, structural loads, and flow field distribution of the FOWT array under different wave incident angles and yaw angles of the first column turbines. The results indicate that the changes in power generation, platform motion, and flow field distribution of the wind farm are significantly influenced by the yaw angle. The maximum tower top yaw bearing torque and the tower base Y-direction bending moment of the wind turbines undergo significant changes with the increase in the angle between wind and wave directions. The study reveals the mechanism of power generation and load variation during yaw control of the FOWT array under misaligned wind and wave conditions, providing a theoretical basis for the future development of offshore floating wind farms. Full article

To address the issue of limited accuracy in vehicle lateral and longitudinal dynamics control—caused by the strong coupling and nonlinearity between the four-wheel steering and distributed drive systems, particularly under crosswind disturbances—a control method integrating differential geometric decoupling with robust control is proposed. This integrated approach mitigates coupling effects among the vehicle motions in various directions, thereby enhancing overall robustness. The control architecture adopts a hierarchical structure: the upper layer takes the deviation between the ideal and actual models as input and generates longitudinal, yaw, and lateral control laws via robust control; the middle layer employs differential geometric methods to decouple the nonlinear system, deriving the total driver-required driving torque, additional yaw moment, and rear-wheel steering angle; and the lower layer utilizes a quadratic programming algorithm to optimize the distribution of driving torque across the four wheels. Finally, simulation verification is conducted based on a co-simulation platform using TruckSim 2022 and MATLAB R2024a/Simulink. The simulation results demonstrate that, compared to the sliding mode control (SMC) and the uncontrolled scenario, the proposed method improves the driving stability and safety of the four-wheel steering distributed drive vehicle under multiple operating conditions. Full article

This study investigates the issue of fault-tolerant motion control in the distributed chassis system (DCS) subject to degradation in independent steering actuators. First, the dynamic behavior of the independent steering system is analyzed to establish a fault-dynamics model for independent steering. The steering powertrain degradation coefficient is then mapped to the contraction of the feasible tire-force region. Subsequently, the model predictive controller (MPC) is designed to solve for the required generalized forces/torques. Moreover, along the direction of the generalized demand force vector, the boundary values for the current cycle are obtained and used to correct the generalized demand force. Finally, an adaptive weighting scheme for the tire force distribution objective function, which accounts for degradation coefficients, is proposed. Sequential quadratic programming (SQP) is employed to achieve optimal utilization of tire forces. Simulation studies for different steering degradation scenarios and road conditions are conducted using a CarSim 2019 and Simulink 2021B co-simulation platform. The simulation results demonstrate that the proposed integrated chassis motion controller maintains excellent motion control performance even under independent steering actuator degradation. Full article

Variations in flight trajectory and velocity during vertical takeoff, transition, and level flight cause substantial changes in the relative inflow vector of multi-rotor unmanned aerial vehicles (UAVs). In urban environments, disturbances from complex wind fields further increase the uncertainty of inflow conditions. This study investigates the aerodynamic characteristics of a fixed-pitch small-sized UAV rotor under varying inflow angles, velocities, and rotational speeds using a subsonic return-flow wind tunnel. The experimental setup enables inflow angle control from −90° to +90° via a turntable. Results indicate that, without incoming flow, the axial thrust and torque coefficients remain nearly constant. With inflow, both coefficients become highly sensitive to velocity in the 2000–5000 rpm range, with deviations up to four times those under static conditions. The in-plane lateral force along the X-axis increases significantly with inflow velocity, reaching about half the axial force, while the Y-axis component is minor and negligible under symmetric configurations. Pitching and rolling moments increase rapidly once inflow velocity exceeds 8 m/s, surpassing the axial torque and exhibiting strong directional asymmetry around ±15° inflow angles. The results demonstrate coupled aerodynamic force and moment behavior of small rotors under complex inflow, providing experimental evidence for improved dynamic modeling, control design, and the energy optimization of UAVs operating in turbulent wind environments. Full article