Search Results (2,539)

Upper-limb motor disabilities and amputation pose a significant burden on individuals, hindering their ability to perform daily activities independently. While various research studies aim to enhance the performance of current upper-limb prosthetic devices, electrically activated prostheses still face challenges in achieving optimal functionality. This paper explores the potential of utilizing electromyogram (EMG) and electroencephalogram (EEG) signals to not only decipher movement across multiple degrees of freedom (DOFs) but also offer a more intuitive means of control. In this study, six distinct control schemes for upper-limb prosthetic devices are proposed, each with different combinations of EEG and EMG signals. These schemes were designed to control multiple degrees-of-freedom movements, encompassing five different hand and forearm actions (hand-open, hand-close, wrist pronation, wrist supination, and rest-state). Using Linear Discriminant Analysis as a model results in classification accuracies of over 85% for combined EEG-EMG control schemes. The results suggest promising advancements in the field and show the potential for a more effective and user-friendly control interface for upper-limb prosthetic devices. Full article

The two-axis coupled electromechanical actuation system (TCEAS) is widely utilized in multiple industrial fields, but its tracking performance and stability are severely hampered by complex nonlinear friction, parameter uncertainties, and strong coupling effects. To address these issues, this paper proposes an adaptive robust stable tracking control (ARSTC) method with friction compensation. First, the friction characteristic of TCEAS is analyzed and a continuously differentiable friction moment function is introduced to accurately describe the nonlinear friction phenomenon. Then, a dynamic analysis model for the system considering friction nonlinearity and model uncertainty is established. Furthermore, the developed ARSTC algorithm leverages adaptive control to estimate and compensate unknown friction parameters (enhancing precision) and robust control to suppress disturbances (ensuring stability). Finally, the superiority is jointly verified by stability analysis and extensive comparative numerical test results. This work demonstrates a practical approach for high-precision control of TCEAS, which has important theoretical significance. Full article

This paper presents a novel methodology for minimizing power losses in brushless DC (BLDC) motors through the implementation of adaptive flux control techniques. Conventional motor control strategies, such as direct torque control (DTC), typically employ fixed flux values, which often result in suboptimal performance, particularly under dynamic load and speed variations. To mitigate this inherent limitation, two adaptive flux control methods are introduced: incremental conductance (IncCond) and fuzzy logic. These proposed strategies facilitate real-time dynamic adjustment of the stator flux, thereby optimizing motor performance and significantly enhancing system efficiency. Experimental validation confirms the efficacy of these adaptive techniques, demonstrating substantial improvements in power loss reduction and overall efficiency when compared to traditional fixed flux control strategies. Notably, the fuzzy logic control strategy achieves the highest efficiency, registering a system efficiency of $66.59$%, which surpasses both the incremental conductance method and conventional fixed flux control. These findings underscore the considerable potential of adaptive flux control in applications where energy efficiency is paramount, including electric vehicles and renewable energy-driven systems. Full article

Electric rope shovels play a critical role in open-pit mining, where their automation and operational efficiency directly affect productivity. This paper presents a LiDAR-based relative positioning method to determine the spatial relationship between the ERS and mining trucks. The method utilizes dynamic DBSCAN for noise removal and RANSAC for truck edge detection, enabling robust and accurate localization. Leveraging this positioning data, a time-optimal trajectory planning strategy is proposed specifically for autonomous swing motion during the unloading process. The planner incorporates velocity and acceleration constraints to ensure smooth and efficient movement, while obstacle avoidance mechanisms are introduced to enhance safety in constrained excavation environments. To execute the planned trajectory with high precision, a neural network-based sliding-mode controller is designed. An adaptive RBF network is integrated to improve adaptability to model uncertainties and external disturbances. Experimental results on a scaled-down prototype validate the effectiveness of the proposed positioning, planning, and control strategies in enabling accurate and autonomous swing operation for efficient unloading. Full article

Given that grinding robots are easily affected by internal and external disturbances when machining complex surfaces with high precision, in this study, an adaptive robust impedance control method combining a radial basis function neural network (RBFNN) and sliding mode control (SMC) is proposed. In a Cartesian coordinate system, we first use the universal approximation ability of the RBFNN to accurately identify and actively compensate for complex unknown disturbances in robot dynamics online. Then, an improved sliding mode impedance controller, which uses robust sliding mode control to effectively suppress the influence of RBFNN identification error and residual disturbance on trajectory tracking and ensure the accuracy of impedance control, is implemented. This approach improves the control performance and overcomes the inherent chattering phenomenon of the traditional sliding mode. Full article

This study presents the design and performance evaluation of an adaptive control system for a biped robot with five degrees of freedom. The primary goal is to achieve stable and accurate control despite uncertainties in the robot’s dynamic parameters and changes in environmental conditions. By analyzing the robot’s dynamic structure, an adaptive control strategy is developed, and its effectiveness is assessed through simulations. The results indicate that the proposed approach delivers superior performance. In particular, the system’s ability to update dynamic parameters in real time significantly reduces tracking errors and ensures the robot’s stability under uncertain conditions. Based on a passivity-based control framework commonly referenced in the literature, the adaptive controller enables precise tracking of desired reference signals, even in complex dynamic environments. Overall, the findings demonstrate that adaptive control is a highly effective solution, especially for complex systems such as biped robots. Full article

As the automotive industry continues to evolve rapidly, there is a growing demand for high-throughput reliable communication systems within vehicles. This paper presents the implementation and verification of a fault-tolerant Ethernet-based communication protocol tailored for automotive applications operating at 1 Gbps and above. The proposed system introduces a multi-port Network Interface Controller (NIC) architecture that supports real-time communication and robust fault handling. To ensure adaptability across various in-vehicle network (IVN) scenarios, the system allows for configurable packet sizes and transmission rates and supports diverse data formats. The architecture integrates cyclic redundancy check (CRC)-based error detection, real-time recovery mechanisms, and file-driven data injection techniques. Functional validation is performed using Verilog HDL simulations, demonstrating deterministic timing behavior, modular scalability, and resilience under fault injection. This paper presents a fault-tolerant Network Interface Controller (NIC), architecture incorporating CRC-based error detection, real-time recovery logic, and file-driven data injection. The system is verified through Verilog HDL simulation, demonstrating correct timing behavior, modular scalability, and robustness against injected transmission faults. Compared to conventional dual-port NICs, the proposed quad-port architecture demonstrates superior scalability and error tolerance under injected fault conditions. Experimental results confirm that the proposed NIC architecture achieves stable multi-port communication under embedded automotive environments. This study further introduces a novel quad-port NIC with an integrated fault injection algorithm and evaluates its performance in terms of error tolerance. Full article

This study focuses on optimizing track and grouser structural parameters to enhance UATV drawbar pull, particularly under soft soil conditions. A numerical soil thrust model for single-track shoes was developed based on track–soil interaction mechanics, revealing distinct mechanistic roles: track structural parameters (length/width) govern pressure–sinkage relationships at the track base, while grouser structural parameters (height, spacing, V-shaped angle) dominate shear stress–displacement dynamics on grouser shear planes. A novel DEM-MBD coupling simulation framework was established through soil parameter calibration and multi-body dynamics modeling, demonstrating that soil thrust increases with grouser height and V-shaped angle, but decreases with spacing, with grouser height exhibiting the highest sensitivity. A soil bin test validated the numerical model’s accuracy and the coupling method’s efficacy. Parametric optimization via the Whale Optimization Algorithm (WOA) achieved a 55.86% increase in drawbar pull, 40.38% reduction in ground contact pressure and 57.33% improvement in maximum gradability. These advancements substantially improve the tractive performance of UATVs in soft beach terrains. The proposed methodology provides a systematic framework for amphibious vehicle design, integrating numerical modeling, high-fidelity simulation, and experimental validation. Full article

With the application of tracked mobile robots in detection and rescue, how to improve their stability and trafficability has become the research focus. In order to improve the driving ability and trafficability of tracked mobile robots in rugged terrain, this paper proposes a new type of tracked mobile robot using passive suspension. By adding a connecting rod differential mechanism between the left and right track mechanisms, the contact stability between the track and terrain is enhanced. The kinematics model and attitude relationship of the suspension are analyzed and established, and the rationality of the passive suspension scheme is verified by dynamic simulation. The simulation results show that the tracked robot with passive suspension shows good obstacle surmounting performance, but there will be a heading deflection problem. Therefore, a track drive speed of the driving state compensation control is proposed based on the driving scene, which can effectively solve the problem of slip and heading deflection. Through the field test of the robot prototype, the effectiveness of the suspension scheme and control system is verified, which provides a useful reference for the scheme design and performance improvement of the tracked mobile robot in complex field scenes. Full article

Electromagnetic pneumatic microvalves, widely used in knitting machines, typically operate based on a spring-return mechanism. When the coil is energized, the electromagnetic force overcomes the spring force to attract the armature, opening the valve. Upon de-energization, the armature returns to its original position under the restoring force of the spring, closing the valve. However, most existing electromagnetic microvalves adopt a radially asymmetric magnetic yoke design, which generates additional radial forces during operation, leading to armature misalignment or even sticking. Additionally, the inductance effect of the coil causes a significant delay in the armature release response, making it difficult to meet the knitting machine’s requirements for rapid response and high reliability. To address these issues, this paper proposes an improved electromagnetic microvalve design. First, the magnetic yoke structure is modified to be radially symmetric, eliminating unnecessary radial forces and preventing armature sticking during operation. Second, a permanent magnet assist mechanism is introduced at the armature release end to enhance release speed and reduce delays caused by the inductance effect. The effectiveness of the proposed design is validated through electromagnetic numerical simulations, and a multi-objective genetic algorithm is further employed to optimize the geometric dimensions of the electromagnet. The optimization results indicate that, while maintaining the fundamental power supply principle of conventional designs, the new microvalve structure achieves a pull-in time comparable to traditional designs during engagement but significantly reduces the release response time by approximately 80.2%, effectively preventing armature sticking due to radial forces. The findings of this study provide a feasible and efficient technical solution for the design of electromagnetic microvalves in textile machinery applications. Full article

Model-based sensorless control of interior permanent-magnet synchronous motors (IPMSMs) typically employs an estimation observer with embedded position information, followed by a position extraction process. Although a type-2 phase-locked loop (PLL) is widely adopted for position and speed extraction, it suffers from steady-state tracking errors under variable-speed operation, leading to torque bias in IPMSM torque control. To mitigate this issue, this paper first proposes an adaptive bandpass full-order observer in the stationary reference frame. Subsequently, a Kalman filter (KF)-based compensation strategy is introduced for the PLL to eliminate tracking errors while maintaining system stability. Experimental validation on a 300 kW platform confirms the effectiveness of the proposed sensorless torque control algorithm, demonstrating significant reductions in position error and torque fluctuations during acceleration and deceleration. Full article

The study of vibration characteristics and suppression methods in integrated electric drive systems of electric vehicles is of critical importance. To investigate these characteristics, both current harmonics within the motor and nonlinear factors within the drivetrain were considered. A 17-degree-of-freedom nonlinear torsional–planar dynamic model was developed, with electromagnetic torque and output speed as coupling terms. The model’s accuracy was experimentally validated, and the system’s dynamic responses were analyzed under different working conditions. To mitigate vibrations caused by torque ripple, a coordinated control strategy was proposed, combining a quasi-proportional multi-resonant (QPMR) controller and a full-frequency harmonic controller (FFHC). The results demonstrate that the proposed strategy effectively suppresses multi-order current harmonics in the driving motor, reduces torque ripple by 45.1%, and enhances transmission stability. In addition, the proposed electromechanical coupling model provides valuable guidance for the analysis of integrated electric drive systems. Full article

Variable-thrust liquid rocket engines are essential for precision landing in deep-space exploration, reusable launch vehicle recovery, high-accuracy orbital maneuvers, and emergency obstacle evasions of space drones. However, with the increasingly complex space missions, challenges remain with the development of different technical schemes. In view of these issues, this paper systematically reviews the technology’s evolution through mechanical throttling, electromechanical precision regulation, and commercial space-driven deep throttling. Then, the development of key variable thrust technologies for liquid rocket engines is summarized from the perspective of thrust regulation and control strategy. For instance, thrust regulation requires synergistic flow control devices and adjustable pintle injectors to dynamically match flow rates with injection pressure drops, ensuring combustion stability across wide thrust ranges—particularly under extreme conditions during space drones’ high-maneuver orbital adjustments—though pintle injector optimization for such scenarios remains challenging. System control must address strong multivariable coupling, response delays, and high-disturbance environments, as well as bottlenecks in sensor reliability and nonlinear modeling. Furthermore, prospects are made in response to the research progress, and breakthroughs are required in cryogenic wide-range flow regulation for liquid oxygen-methane propellants, combustion stability during deep throttling, and AI-based intelligent control to support space drones’ autonomous orbital transfer, rapid reusability, and on-demand trajectory correction in complex deep-space missions. Full article

This paper presents a comparative analysis of electric field (E-field) mitigation in inductive power transfer (IPT) systems. It focuses on how distributed capacitor placement interacts with coil topology to influence E-field emissions. The study compares traditional sequential-winding coils and the alternating voltage phase coil (AVPC), which employs a sequential inversion winding (SIW) structure to enforce a 180° phase voltage opposition between adjacent turns. While capacitor segmentation is a known method for E-field reduction, this work is the first to systematically evaluate its effects across both conventional and phase-inverted coils. The findings reveal that capacitor placement serves as a topology-dependent design parameter. Finite Element Method (FEM) simulations and experimental validation show that while capacitor placement has a moderate influence on traditional coils due to in-phase voltage relationships, AVPC coils are highly sensitive to segmentation patterns. When capacitors align with the SIW phase structure, destructive interference significantly reduces E-field emissions. Improper capacitor placement disrupts phase cancellation and negates this benefit. This study resolves a critical design gap by establishing that distributed compensation acts as a tuning mechanism in conventional coils but becomes a primary constraint in phase-inverted topologies. The results demonstrate that precise capacitor placement aligned with the coil topology significantly enhances E-field mitigation up to 60% in AVPC coils, greatly outperforming traditional coil configurations and providing actionable guidance for high-power wireless charging applications. Full article

This study presents the state-feedback and output-feedback adaptive shared trajectory tracking control laws for nonlinear Euler–Lagrange systems subject to parametric uncertainties and output constraints framed within linear inequalities. The logarithm-driven coordinate transformation is used to ensure that system outputs are consistently bounded by defined regions, while model-based adaptive laws are used in the machine controller to estimate and cancel parametric uncertainties and the human controller can be given arbitrarily. The stability of the whole controlled system is proved by Lyapunov stability theory, and simulation examples are used to illustrate the performance of the proposed shared control laws. Full article