Search Results (1,442)

Permanent magnet synchronous motor (PMSM)-based servo actuators are fundamental to high-performance electromechanical systems. However, in energy-sensitive aerospace applications, the impact of tracking error on system-level efficiency remains insufficiently quantified. This paper establishes an energy-oriented analytical framework linking PMSM tracking accuracy to vehicle-level energy consumption and flight range. By employing a specific mechanical energy formulation, we demonstrate that tracking deviations modify aerodynamic drag and introduce additional dissipative work. Specifically, the accumulated dissipation is shown to admit a lower bound proportional to the integral of the squared tracking error, from which a range degradation bound is derived. These results reveal that “tracking-error energy” imposes a fundamental limit on achievable flight distance. A Lyapunov-based analysis further proves that minimizing this error energy reduces total aerodynamic dissipation without requiring modifications to propulsion scheduling or guidance laws. Numerical simulations comparing a conventional sliding mode controller with an advanced fuzzy-adaptive nonsingular terminal sliding mode controller confirm that enhanced servo precision directly improves velocity retention and range performance. This framework offers practical insights for designing energy-aware PMSM control strategies in energy-constrained aerospace platforms. Full article

High-precision time and frequency references are essential for satellite navigation, deep-space exploration, and space science missions. To address the large size, high power consumption, and limited integration of conventional Passive Hydrogen Maser (PHM) servo electronics based on discrete analog chains, this paper proposes a miniaturized digital servo architecture for PHMs based on software-defined radio (SDR) and a field-programmable gate array (FPGA). The AD9364 is used as an integrated RF front end for microwave interrogation signal generation, receiver down-conversion, and analog-to-digital conversion (ADC), while digital demodulation, discriminator construction, and closed-loop control are implemented in the FPGA. A dual-frequency interrogation and time-division multiplexing scheme is introduced to separate the atomic and cavity responses, and an oversampling-based processing method combining outlier rejection and averaging decimation is adopted to improve the observation accuracy and noise immunity of weak error signals. Experimental results demonstrate stable closed-loop locking of the atomic transition spectrum, achieving a frequency stability of 1.46 × 10⁻¹² at 1 s, while significantly improving the compactness and integration level of the servo electronics. Full article

The gimbal servo system in a control moment gyroscope (CMG) is critical for high-precision spacecraft attitude control, where comprehensive performance testing and evaluation are essential for ensuring spacecraft reliability and service life. Traditional motor testbenches exhibit limitations, whereas the electric motor emulator (EME) based on power electronic converters is a promising alternative for testing extreme operating conditions, such as ultra-low speed operation and fault scenarios. However, existing EME control methods suffer from limited system bandwidth and insufficient emulation accuracy, which limits their applicability. To address these issues, this paper proposes an improved current control strategy for the ultra-low speed permanent magnet synchronous motor (PMSM) emulator. First, a mathematical model of the EME based on the topology of the voltage source converter is established. Then, based on the deadbeat control concept, a deadbeat predictive current control (DPCC) strategy is developed to enhance the dynamic performance. Furthermore, to suppress the parameter mismatch disturbance, an optimization scheme based on a cascaded extended state observer (CESO) is introduced. The first-stage ESO is applied to estimate and compensate for total disturbances, while the second-stage ESO is a supplement to suppress the remaining disturbances in the EME system, which improves the robustness of the DPCC controller. Finally, the effectiveness of the improved emulation accuracy of the proposed method is verified through experiments. Full article

A novel data-driven modeling framework is developed for servo control using Long Short-Term Memory (LSTM) networks. The framework employs an LSTM model to directly map interpolation commands and feedback signals, such as velocity, acceleration, and jerk, to tracking errors. By adopting end-to-end architecture, the method bypasses complex sequential procedures, including system identification and friction modeling, significantly reducing development time and modeling complexity. Experimental results demonstrate that the LSTM model accurately predicts servo tracking behavior and enables rapid performance evaluation and parameter optimization without performing time-consuming trajectory testing. The proposed framework offers a practical and efficient alternative to traditional model-based techniques in precision motion control. Full article

Currently, most mobile manipulators employ a “Stop-and-Grasp” strategy, where the base of the manipulator stops before the arm executes the grasp. However, achieving “Grasping-on-the-Move” actions—where the robot grasps a target while the base is in motion—remains a significant challenge due to the coupling of base and arm dynamics. To address this, we propose a two-phase collaborative motion planning framework. In the first phase (long-range approach), we introduce a spatially constrained visual servoing (SC-VS) method. By establishing a dynamic safety corridor based on the chassis path, this method ensures robust target tracking and obstacle avoidance for the arm during base motion. In the second phase (close-range grasping), to seize the brief grasping opportunity, we propose a Constrained-Sampling RRT-Connect (CSR-RRT-Connect) algorithm. By restricting the sampling region based on target prediction, this algorithm significantly reduces planning time. Comparative experiments demonstrate that our method achieves a 92% success rate at a base speed of 0.3 m/s, significantly outperforming the 46% success rate of baseline methods, while exhibiting superior robustness against dynamic operational disturbances and perception noise. Full article

(1) Background: Early treatment of sleep-disordered breathing (SDB) with adaptive servo-ventilation (ASV) after acute myocardial infarction (AMI) has been shown to improve myocardial salvage. This analysis evaluates nocturnal electrocardiogram (ECG) Holter data, derived from polygraphy in a randomised clinical trial (NCT02093377), to assess the occurrence of nocturnal cardiac arrhythmias in patients with SDB and to explore the effect of ASV therapy. (2) Methods: In the TEAM-ASV I trial, patients were stratified by the presence/absence of SDB, defined by an apnoea–hypopnoea index (AHI) ≥15 events/h assessed with polygraphy. Those with SDB were subsequently randomised to receive ASV in addition to standard AMI care. Guideline-conforming semi-automated ECG analysis of nocturnal cardiac arrhythmias was conducted via Holter–ECG software (custo diagnostic, version 5.4). (3) Results: Patients with SDB had an increased incidence of non-sustained ventricular tachycardia (NSVT) (SDB: n = 8 (16%) vs. no SDB: n = 1 (2%); p = 0.024) and premature atrial contractions (PAC) (SDB: 1.2/h [0.3, 3.4] vs. no SDB: 0.3/h [0.1, 1.2]; p = 0.017). In patients with SDB who were randomised to ASV treatment early after AMI, we found no reduction in cardiac arrhythmias when ASV was added to standard care. (4) Conclusions: After AMI, SDB was linked to increased NSVT and PAC. ASV treatment demonstrated neither a harmful nor a beneficial effect on the occurrence of nocturnal cardiac arrhythmias. Further trials are warranted to confirm these findings. Full article

To investigate the seepage and mechanical behavior of the overlying strata during solution mining in salt deposits, porous sandstones with different grain sizes were selected for study. First, a series of microscopic tests, including SEM, MIP, and NMR, was conducted to characterize the pore structure of the rocks. Subsequently, using a servo-controlled triaxial rock testing system, permeability tests covering the complete stress–strain process were performed under different confining pressures and seepage pressures based on the steady-state method, in order to analyze the seepage and mechanical characteristics of the sandstones during deformation and failure. The results indicate that the investigated aquifer sandstones are characterized by weak cementation, high porosity, large pore size, good pore connectivity, and relatively high permeability. High confining pressure enhances the mechanical strength of the sandstone while reducing its permeability, whereas increasing seepage pressure decreases mechanical strength and enhances permeability during triaxial compression under pore water pressure conditions. Throughout the complete stress–strain process, the evolution of permeability is jointly controlled by the intrinsic pore structure of the rock, the stress loading path, and the failure mode. Under high confining pressure, localized compaction bands may develop, and the formation of such localized structures suppresses any increase in permeability. Acoustic emission shows good correlations with both the stress–strain response and permeability evolution. This study provides new insights into the pore structure of loose, highly permeable sandstones and their hydromechanical coupling behavior throughout the complete stress–strain process. Full article

Hydraulic manipulators face critical challenges due to valve dead-band nonlinearity and state constraints, which can lead to safety hazards and hardware damage. This study proposes a state-constrained controller with valve dead-band compensation to ensure prescribed positioning accuracy and operational safety. Barrier Lyapunov functions ensure that state constraints are maintained and that boundary violations are avoided. Concurrently, a smooth dead-band inverse model is developed to offset asymmetric valve dead-band effects without inducing chatter. Adaptive laws estimate uncertain parameters and dead-band impact in real time, and a disturbance observer attenuates unmatched uncertainties. Dynamic surface control is employed to diminish the explosion of complexity in backstepping design. Comparative simulations under fixed-angle and arbitrary-angle tracking demonstrate that the proposed controller achieves superior tracking accuracy with steady-state errors below 0.04° compared to 0.06° for non-compensated controllers, while significantly reducing pressure fluctuations and control chattering as adaptive parameters converge. The results indicate that the strategy effectively compensates for valve dead zones while strictly maintaining state constraints, thereby achieving the required control precision for hydraulic servo systems. Full article

A novel hydraulic circuit, the Modular Hydraulic Servo Booster (MHSB) is applied to redundant hydraulic manipulators. The MHSB uses multiple pumps and valves to drive multiple actuators to significantly improve energy efficiency compared with conventional servo-valve systems. Our previous work has proposed a control strategy that incorporates energy-optimal trajectory planning and operation mode switching using a graph search algorithm to perform point-to-point (PTP) tasks for manipulators. This paper extends our previous study by constructing an optimal-posture table that incorporates manipulability. By using this table to evaluate the cost in graph search, we achieve real-time optimal trajectory planning and operation mode switching for redundant manipulators. Numerical simulation from different PTP tasks on a three-link manipulator (1-m length, 10-kg weight) validate the proposed method. Full article

Airborne electromagnetic detection systems are highly susceptible to low-frequency motion-induced noise, which significantly degrades the extraction of weak geological signals. Conventional signal processing methods alone are often insufficient to suppress mechanically induced vibration noise, resulting in signal distortion and reduced detection reliability. To address this limitation, this study proposes an active noise suppression strategy that integrates mechanical vibration isolation with advanced signal processing. A pneumatic vibration isolation platform based on a cable-driven parallel robot (CDPR) architecture is developed to achieve precise orientation correction and effective vibration isolation. The system employs kinematic modeling and a servo-controlled pneumatic cylinder driven by a proportional directional valve to enable accurate dynamic regulation. Numerical simulations conducted in the Advanced Modeling and Simulation Environment (AMESim), combined with proportional–integral–derivative (PID) control, demonstrate that piston displacement overshoot is constrained within 0.2 mm. Furthermore, targeted filtering techniques are applied to enhance signal quality. Experimental results show that the response time for continuous step input is 0.18–0.2 s, with a steady-state error below 0.3 mm, confirming robust control performance. The proposed framework provides an effective low-noise solution for airborne electromagnetic detection and can improve survey reliability in deep resource exploration. Full article

With the intensification of global agricultural labor shortage and scaled development of facility agriculture, autonomous precision harvesting robots for unstructured greenhouse environments have become an urgent need. For cluster-picking crops such as tomatoes, visual servoing enables real-time closed-loop control of the end-effector pose, addressing challenges of random fruit distribution and variable stem orientations. However, existing methods struggle to balance constraint handling with real-time efficiency. This paper proposes an MPC-Guided Reinforcement Learning visual servoing framework, innovatively combining the planning capability of optimal control with the adaptive learning ability and real-time inference advantages of reinforcement learning. The approach adopts a teacher–student paradigm: expert trajectories from the MPC controller warm-start the reinforcement learning policy through behavior cloning, followed by PPO-based fine-tuning with adaptive gain regulation and stagnation-enhanced exploration mechanisms. Simulation experiments demonstrate a 95% success rate with average positioning and orientation errors of 13.6 mm and 0.009 rad respectively. Compared to MPC baseline, task steps are reduced by 53.4%; compared to Standard PPO, success rate improves by 6%. Greenhouse field validation achieves 85.3% picking success rate and 5.63 s per fruit operation time, confirming the framework’s excellent balance among control precision, robustness, and efficiency for high-precision robotic harvesting in unstructured agricultural environments. Full article

This paper presents the design and implementation of a real-time visual tracking system for unmanned aerial vehicles (UAVs), based on the DJIPayload Software Development Kit (PSDK), addressing the challenge of balancing high precision with low latency on resource-constrained edge platforms. By utilizing DJI PSDK to abandon the Robot Operating System (ROS) layer and its associated serialization overhead, the proposed Middleware-Free Architecture reduces end-to-end latency by over 60% to approximately 30 ms. To address computational constraints, a Lightweight Asymmetric De-coupled Visual Servoing (ADVS) strategy is proposed. It adopts orthogonal kinematic de-coupling to bypass Jacobian matrix inversion and integrates a non-linear dead-zone mechanism with dynamics-aware gain scheduling to compensate for sensing anisotropy and gravitational nonlinearity. Simultaneously, a Geometry-Aware Fusion strategy is employed to reject visual outliers, while a Finite State Machine (FSM) strictly enforces temporal consistency. Field experiments in various scenarios verify the system’s stability and tracking capability. Specifically, the platform maintains a robust lock on targets at speeds up to 23 m/s across dynamic maneuvers. The successful implementation of this system confirms that high-performance edge tracking does not rely solely on the scaling of visual model complexity but can also be effectively achieved through the architectural minimization of latency combined with the optimization of theoretically grounded robust control strategies. Full article

Stable wind resources in far-reaching sea areas are important direction for the development of renewable energy, making floating offshore wind turbine (FOWT) a focus of current research. However, the working environment of FOWT is severe. Under the condition of changeable wind and waves, the floating platform exhibits various motion responses, which may reduce power generation efficiency and even lead to structural damage with unpredictable consequences. In this paper, the National Renewable Energy Laboratory (NREL) 5 MW OC4-DeepCwind semi-submersible wind turbine is considered, and a multi-degree-of-freedom (M-DOF) tuned mass damper (TMD) system is designed to simultaneously suppress its roll and pitch motion responses. A multi-objective optimization problem is formulated to unify the frequency tuning accuracy, damping ratio constraints, and mass ratio limits through penalty functions. Then an improved Particle Swarm Optimization algorithm with time-varying acceleration coefficients (TVAC-PSO) is employed to determine the optimal TMD parameters, which dynamically adjusts exploration and exploitation capabilities to overcome the limitations of standard PSO in handling the strongly coupled parameter space. A high-fidelity aero-hydro-servo-elastic simulation model is established using OpenFAST to verify the vibration suppression performance under various sea state conditions. Simulation results demonstrate that the proposed M-DOF TMD system can effectively reduce the roll and pitch motion responses and significantly suppress the resonant peak energy, substantially improving the dynamic performance of FOWT. Full article

The growing need for remote patient monitoring, accelerated by the global pandemic and an aging population, necessitates the development of advanced non-contact technologies for measuring vital signs. In this study, an integrated, non-contact system for accurately measuring heart rate (HR) and body temperature (BT) is developed and validated. The proposed system combines a 60 GHz radar sensor and infrared (IR) sensor for HR and BT measurements, respectively, enhanced with advanced signal processing and an AI-based computer vision algorithm. A Window Filter and a Peak Uniformity algorithm were applied to the raw radar signal to mitigate noise and motion artifacts. For Temp measurement, an IR sensor with a narrow five-degree field of view (FOV) was integrated with a YOLO Pose-based tracking system using a camera and servo motors to automatically orient the sensor towards the user’s face. The system was validated with 30 healthy adult participants, benchmarked against a MAX30102 PPG sensor and Braun ThermoScan 7 for BT and BT measurements, respectively. The advanced signal processing reduced the HR Mean Absolute Error from 13.73 BPM to 5.28 BPM (p = 0.002), while the AI-guided IR sensor reduced the BT MAE from 4.10 °C to 1.64 °C (p < 0.001). These findings demonstrate that integrating 60 GHz radar with AI-driven tracking provides a promising approach for home-based trend monitoring. Full article

One of the key factors determining energy consumption and control stability in hydraulic servovalves with direct electric drive is the flow forces acting on the spool. These forces are complex in nature and consist of both steady-state and transient components, with the steady-state component exerting the dominant influence on the performance and dynamics of spool valves. In recent years, this issue has become the subject of intensive research aimed at reducing undesirable hydraulic loads while maintaining high nominal flow capacity, strong energy efficiency, and low manufacturing cost. In engineering practice, the most effective approach has proven to be the modification of the spool geometry in order to control the direction and jet angle of the outflow while keeping the valve sleeve design as simple as possible. This solution reduces the forces acting on the spool without the need to redesign the flow channels or increase production complexity. This study presents classical analytical methods used to calculate flow forces in typical spool valve designs, which serve as a reference point for subsequent investigations. Then, using CFD simulation tools, a method of flow force compensation is demonstrated for selected spool geometries, followed by a detailed comparative analysis of their effectiveness. The results may provide a foundation for developing more energy-efficient and dynamically stable direct-drive servovalve constructions. Full article