Search Results (306)

Nonlinear narrowband low-frequency noise generated during tractors’ operation significantly affects operators’ comfort and working efficiency. Traditional linear active noise control algorithms often struggle to effectively suppress such complex acoustic disturbances. To address this challenge, this paper proposes a momentum-enhanced Volterra filter-based active noise control (ANC) algorithm that improves both the modeling capability of nonlinear acoustic paths and the convergence performance of the system. The proposed approach integrates the nonlinear representation power of the Volterra filter with a momentum optimization mechanism to enhance convergence speed while maintaining robust steady-state accuracy. Simulations are conducted under second- and third-order nonlinear primary paths, followed by performance validation using multi-tone signals and real in-cabin tractor noise recordings. The results demonstrate that the proposed algorithm achieves superior performance, reducing the NMSE to approximately −35 dB and attenuating residual noise energy by 3–5 dB in the 200–800 Hz range, compared to FXLMS and VFXLMS algorithms. The findings highlight the algorithm’s potential for practical implementation in nonlinear and narrowband active noise control scenarios within complex mechanical environments. Full article

Objectives: Saffron, a traditional Chinese medicine, is renowned for its pharmacological effects in promoting blood circulation, resolving blood stasis, regulating menstruation, detoxification, and alleviating mental disturbances. Trans-crocetin, its principal bioactive component, exhibits significant anti-hypoxic activity. The clinical development and therapeutic efficacy of trans-crocetin are limited by its instability, poor solubility, and low bioavailability. Conversion of trans-crocetin into trans-sodium crocetinate (TSC) enhances its solubility, stability, and bioavailability, thereby amplifying its anti-hypoxic potential. Methods: This study integrates network pharmacology with in vivo and in vitro validation to elucidate the molecular targets and mechanisms underlying TSC’s therapeutic effects against high-altitude acute lung injury (HALI), aiming to identify novel treatment strategies. Results: TSC effectively reversed hypoxia-induced biochemical abnormalities, ameliorated lung histopathological damage, and suppressed systemic inflammation and oxidative stress in HALI rats. In vitro, TSC mitigated CoCl₂-induced hypoxia injury in human pulmonary microvascular endothelial cells (HPMECs) by reducing inflammatory cytokines, oxidative stress, and ROS accumulation while restoring mitochondrial membrane potential. Network pharmacology and pathway analysis revealed that TSC primarily targets the EGFR/PI3K/AKT/NF-κB signaling axis. Molecular docking and dynamics simulations demonstrated stable binding interactions between TSC and key components of this pathway. ELISA and RT-qPCR confirmed that TSC significantly downregulated the expression of EGFR, PI3K, AKT, NF-κB, and their associated mRNAs. Conclusions: TSC alleviates high-altitude hypoxia-induced lung injury by inhibiting the EGFR/PI3K/AKT/NF-κB signaling pathway, thereby attenuating inflammatory responses, oxidative stress, and restoring mitochondrial function. These findings highlight TSC as a promising therapeutic agent for HALI. Full article

This paper proposes a coordinated control strategy for grid-forming inverters (GFMs) to address two critical challenges in evolving power systems. These are the active harmonic mitigation under nonlinear loading conditions and dynamic overcurrent control during grid disturbances. The proposed framework integrates a shunt active filter (SAF) mechanism within the GFM control structure to achieve a real-time suppression of harmonic distortions from the inverter and grid currents. In parallel, a virtual impedance-based dynamic current limiting strategy is incorporated to constrain fault current magnitudes, ensuring the protection of power electronic components and maintaining system stability. The SAF operates in a current-injection mode aligned with harmonic components, derived via instantaneous reference frame transformations and selective harmonic extraction. The virtual impedance control (VIC) dynamically modulates the inverter’s output impedance profile based on grid conditions, enabling adaptive response during fault transients to limit overcurrent stress. A detailed analysis is performed for the coordinated control of the grid-forming inverter. Supported by simulations and analytical methods, the approach ensures system stability while addressing overcurrent limitations and active harmonic filtering under nonlinear load conditions. This establishes a viable solution for the next-generation inverter-dominated power systems where reliability, power quality, and fault resilience are paramount. Full article

The present study analyzes the global ionospheric response to the intense geomagnetic storm of 10–11 October 2024 (SYM—H minimum of −346 nT), using observations from COSMIC—2 and Swarm satellites, GNSS TEC, and Digisondes. Significant uplift of the F-region was observed across both Hemispheres on the dayside, primarily driven by equatorward thermospheric winds and prompt penetration electric fields (PPEFs). However, this uplift did not correspond with increases in foF2 due to enhanced molecular nitrogen-promoting recombination in sunlit regions and the F2 peak rising beyond the COSMIC—2 detection range. In contrast, in the Southern Hemisphere nightside ionosphere exhibited pronounced Ne depletion and low hmF2 values, attributed to G-conditions and thermospheric composition changes caused by storm-time circulation. Strong vertical plasma drifts exceeding 100 m/s were observed during both the main and recovery phases, particularly over Ascension Island, driven initially by southward IMF—Bz-induced PPEFs and later by disturbance dynamo electric fields (DDEFs) as IMF—Bz turned northward. Swarm data revealed a poleward expansion of the Equatorial Ionization Anomaly (EIA), with more pronounced effects in the Southern Hemisphere due to seasonal and longitudinal variations in ionospheric conductivity. Additionally, the storm excited Large-Scale Travelling Ionospheric Disturbances (LSTIDs), triggered by thermospheric perturbations and electrodynamic drivers, including PPEFs and DDEFs. These disturbances, along with enhanced westward thermospheric wind and altered zonal electric fields, modulated ionospheric irregularity intensity and distribution. The emergence of anti-Sq current systems further disrupted quiet-time electrodynamics, promoting global LSTID activity. Furthermore, storm-induced equatorial plasma bubbles (EPBs) were observed over Southeast Asia, initiated by enhanced PPEFs during the main phase and suppressed during recovery, consistent with super EPB development mechanisms. Full article

This study introduces a rigid–flexible coupled constant force actuator integrated with Active Disturbance Rejection Control (ADRC) to tackle the rigidity–compliance trade-off in precision force-sensitive applications. The actuator utilizes compliant hinges to decrease contact stiffness by three orders of magnitude (${10}^6\to {10}^3 \mathrm{N}/\mathrm{m}$), facilitating effective force management through millimeter-scale placement (0.1∼1 mm) and inherently mitigating high-frequency disturbances. The ADRC framework, augmented by an Extended State Observer (ESO), dynamically assesses and compensates for internal nonlinearities (such as friction hysteresis) and external disturbances without necessitating accurate system models. Experimental results indicate enhanced performance compared to PID control: under dynamic disturbances, force deviations are limited to $\pm 0.2 \mathrm{N}$ with a 98.5% reduction in mean absolute error, a 96.3% increase in settling speed, and 99% suppression of oscillations. The co-design of mechanical compliance with model-free control addresses the constraints of traditional high-stiffness systems, providing a scalable solution for industrial robots, compliant material processing, and medical device operations. Validation of the prototype under sinusoidal perturbations demonstrates reliable force regulation (settling time $<0.56 \mathrm{s}$, errors $<0.5 \mathrm{N}$), underscoring its relevance in dynamic situations. This study integrates theoretical innovation with experimental precision, enhancing intelligent manufacturing systems via adaptive control and structural synergy. Full article

The hybrid maglev train exhibits advantages such as a large suspension gap, high load-to-weight ratio, and low suspension energy consumption. However, challenges, including unmodeled uncertainties and multi-point coupling interference in the suspension system, may degrade control performance. To enhance the global anti-interference capability of the multi-point hybrid suspension system, an adaptive linear active disturbance rejection cooperative control (ALADRCC) method is proposed. First, dynamic models of single-point and multi-point hybrid suspension systems are established, and coupling relationships among multiple suspension points are analyzed. Second, an adaptive linear extended state observer (ALESO) is designed to improve dynamic response performance and noise suppression capability. Subsequently, a coupling cooperative compensator (CCC) is designed and integrated into the linear error feedback control law of adaptive linear active disturbance rejection control (ALADRC), enabling cross-coupling compensation between the suspension gap and its variation rate to enhance multi-point synchronization. Then, the simulation models are constructed on MATLAB/Simulink to validate the effectiveness of ALESO and CCC. Finally, a multi-point hybrid suspension experimental platform is built. Comparative experiments with PID and conventional LADRC demonstrate that the proposed ALADRC achieves faster response speed and effective system noise suppression. Additional comparisons with PID and ALADRC confirm that ALADRCC significantly reduces synchronization errors between adjacent suspension points, exhibiting superior global anti-interference performance. Full article

Focused on the contradiction between the steady-state error of active power and the dynamic oscillation caused by the virtual damping characteristics of the virtual synchronous generator (VSG) under disturbances during grid-connected operation, this article proposes an adaptive virtual inertia regulation and compensation method (PFFCVSG_AJ) based on an active power differential feedforward compensation strategy (PFFCVSG). Firstly, this article presents the working and control principles of VSG, analyzing its control mechanisms through a small-signal model. Models for VSG’s active power, reactive power, and virtual impedance components are established, with particular focus on the impact of the damping coefficient on active power regulation. Based on the PFFCVSG, an adaptive virtual inertia adjustment method is introduced to resolve the inherent inertia deficiency in PFFCVSG control, the influence of the moment of inertia on PFFCVSG is theoretically analyzed, and a dynamic adjustment mechanism for moment of inertia is developed based on the rate of change in frequency (RoCoF). Finally, simulation validation using MATLAB/Simulink (MathWorks, R2022b, Natick, MA, USA) demonstrates that the proposed PFFCVSG_AJ strategy effectively eliminates active power steady-state deviation, suppresses active power dynamic oscillation, and mitigates the frequency overshoot issue prevalent in traditional PFFCVSG. Experimental verification is conducted via a TMS320F28378DPTPS-based control platform, confirming the algorithm’s effectiveness under sudden load variations, and that the power quality of the power grid is not affected under the premise of efficient grid connection. Full article

Cancer therapy-induced hypertension (HTN) is an increasingly recognized complication associated with a wide range of anticancer agents, including vascular endothelial growth factor (VEGF) inhibitors, proteasome inhibitors, tyrosine kinase inhibitors, and alkylating agents. The pathogenesis of HTN in this setting is multifactorial, involving mechanisms such as endothelial dysfunction, nitric oxide (NO) suppression, sympathetic nervous system activation, and vascular remodeling. Additional factors, including paraneoplastic syndromes, poorly controlled pain, mood disturbances, and overlapping cardiovascular risk factors like obesity and diabetes, further contribute to the complexity of diagnosis and management. Despite its prevalence and clinical implications, cancer therapy-induced HTN is often addressed using general population guidelines, with limited oncology-specific protocols available. Accurate blood pressure measurement and individualized treatment plans are critical to optimize outcomes and avoid interruptions to cancer therapy. Antihypertensive agents such as angiotensin-converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARB), and calcium channel blockers have shown efficacy in both blood pressure control and, in some cases, oncologic outcomes. A multidisciplinary approach involving oncologists, cardiologists, and primary care providers is essential to navigate the interplay between cancer treatment and cardiovascular health. Ongoing research is needed to develop targeted guidelines and improve the long-term care of cancer patients affected by treatment-induced HTN. Full article

This study addresses the challenge of ride height control in linear motor-based active suspension systems by proposing a control strategy based on linear active disturbance rejection control (LADRC). The effectiveness of the proposed approach is experimentally validated using a high-precision test platform built on the NI cRIO-9014 real-time controller. The platform integrates a permanent magnet synchronous linear motor, a motor driver, acceleration sensors, and a vibration control system to realize closed-loop control of vehicle body height. Experimental results demonstrate that, compared with conventional PID control, LADRC achieves superior performance in height regulation accuracy, dynamic responsiveness, vertical acceleration suppression, and steady-state stability. In step response experiments, LADRC reduces the regulation time by 53.8% (from 1.3 s to 0.6 s) and lowers the steady-state error from 0.502 mm to 0.05 mm. In sinusoidal trajectory tracking tests, the LADRC approach reduces peak and RMS tracking errors by 81.5% and 80.3%, respectively. Moreover, under random road excitation, LADRC effectively attenuates high-frequency body vibrations, with reductions of 29.58% in peak vertical acceleration and 12.23% in RMS acceleration. Full article

Traditional control strategies for vibration suppression primarily focus on reducing settling time. However, this approach may not adequately address situations where the initial peak response of the vibration poses a risk of damage. This paper presents a novel application of active disturbance rejection control (ADRC) for attenuating the first-cycle peak response of free vibration in flexible structures. Inspired by the sudden impact scenario of particle accelerator collimators, a smart beam was designed to investigate the percentage first-cycle peak attenuation (FCPA) achievable by the disturbance estimation-based controller, in comparison with a classical proportional–differential (PD) controller. This study examined the limitations of the controller in mitigating initial deviations caused by real-world factors, such as delay and noise, through experimental methods. Results indicate that the PD controller achieves a maximum attenuation of 18%, while the ADRC achieves 30% attenuation. Improving the collocation configuration of the smart beam further improves the ADRC attenuation to 46.5%. Experimental data was used to fine-tune the system model in a sensitivity analysis to determine the delay within the system. Additionally, a new tuning parameter, α, representing the ratio of the observer bandwidth to controller bandwidth, was introduced to investigate the impact of observer and controller gain choices. System noise was amplified by 20 to 30 times, depending on the α value, although no significant effect on the control of the beam was observed. Full article

This paper proposes an integrated control framework for improving the trajectory tracking performance of autonomous ground electric vehicles (AGEVs) under complex disturbances, including parameter uncertainties, and environmental changes. The framework integrates active disturbance rejection control (ADRC) for real-time disturbance estimation and compensation with a deep deterministic policy gradient (DDPG)-based deep reinforcement learning (DRL) algorithm for dynamic optimization of controller parameters to improve tracking accuracy and robustness. More specifically, it combines the Line of Sight (LOS) guidance rate with ADRC, proves the stability of LOS through the Lyapunov law, and designs a yaw angle controller, using the extended state observer to reduce the impact of disturbances on tracking accuracy. And the approach also addresses the nonlinear vehicle dynamic characteristics of AGEVs while mitigating internal and external disturbances by leveraging the inherent decoupling capability of ADRC and the data-driven parameter adaptation capability of DDPG. Simulations via CarSim/Simulink are carried out to validate the controller performance in serpentine and double-lane-change maneuvers. The simulation results show that the proposed framework outperforms traditional control strategies with significant improvements in lateral tracking accuracy, yaw stability, and sideslip angle suppression. Full article

Reverberation is the primary interference of active detection. Therefore, the effective suppression of reverberation is a prerequisite for reliable signal processing. Existing dereverberation methods have shown effectiveness in specific scenarios. However, they often struggle to exploit the distinction between target echo and reverberation, especially in complex, dynamically changing underwater environments. This paper proposes a novel dereverberation network, ERCL-AttentionNet (Echo–Reverberation Complementary Learning Attention Network). We use the Continuous Wavelet Transform (CWT) to extract time–frequency features from the received signal, effectively balancing the time and frequency resolution. The real and imaginary parts of the time–frequency matrix are combined to generate attention representations, which are processed by the network. The network architecture consists of two complementary UNet models sharing the same encoder. These models independently learn target echo and reverberation features to reconstruct the target echo. An attention mechanism further enhances performance by focusing on target information and suppressing irrelevant disturbances in complex environments. Experimental results demonstrate that our method achieves a higher Peak-to-Average Signal-to-Reverberation Ratio (PSRR), Structural Similarity Index (SSIM), and Peak-to-Average Ratio (PAR) of cross-correlation while effectively preserving key time–frequency features, compared to traditional methods such as autoregressive (AR) and singular value decomposition (SVD). Full article

Hydraulically driven flexible robotic arms (HDFRAs) play an indispensable role in industrial precision operations such as aerospace assembly and nuclear waste handling, owing to their high power density and adaptability to complex environments. However, inherent mechanical flexibility-induced vibrations, hydraulic nonlinear dynamics, and electromechanical coupling effects lead to multi-timescale control challenges, severely limiting high-precision trajectory tracking performance. The present study introduces a novel hierarchical control framework employing dual-timescale perturbation analysis, which effectively addresses the constraints inherent in conventional single-timescale control approaches. First, the system is decoupled into three subsystems via dual perturbation parameters: a second-order rigid-body motion subsystem (SRS), a second-order flexible vibration subsystem (SFS), and a first-order hydraulic dynamic subsystem (FHS). For SRS/SFS, an adaptive fast terminal sliding mode active disturbance rejection controller (AFTSM-ADRC) is designed, featuring a dual-bandwidth extended state observer (BESO) to estimate parameter perturbations and unmodeled dynamics in real time. A novel reaching law with power-rate hybrid characteristics is developed to suppress sliding mode chattering while ensuring rapid convergence. For FHS, a sliding mode observer-integrated sliding mode coordinated controller (SMO-ISMCC) is proposed, achieving high-precision suppression of hydraulic pressure fluctuations through feedforward compensation of disturbance estimation and feedback integration of tracking errors. The globally asymptotically stable property of the composite system has been formally verified through systematic Lyapunov-based analysis. Through comprehensive simulations, the developed methodology demonstrates significant improvements over conventional ADRC and PID controllers, including (1) joint tracking precision reaching ${10}^{-4}$ rad level under nominal conditions and (2) over 40% attenuation of current oscillations when subjected to stochastic disturbances. These results validate its superiority in dynamic decoupling and strong disturbance rejection. Full article

Achieving excellent speed control in permanent magnet synchronous motors (PMSMs) relies on the simultaneous suppression of both aperiodic and periodic disturbances. This paper presents an enhanced Active Disturbance Rejection Control (ADRC) strategy specifically designed to address these disturbances in single-rotor compressors (SRCs). To achieve simultaneous suppression, a Recursive Gauss–Newton (RGN) algorithm is implemented in parallel with the conventional extended state observer (ESO) to enhance the ADRC framework. The RGN algorithm iteratively estimates the amplitude and phase information of periodic disturbances, while the ESO primarily observes the system’s aperiodic disturbances. In contrast to existing methods, the proposed angle-based approach demonstrates superior performance during speed transients. Detailed convergence and decoupling analyses are provided to facilitate parameter tuning. The effectiveness of the proposed method is validated through simulations and experiments conducted on a 650 W SRC, demonstrating its superiority over proportional–integral (PI) control, conventional ADRC, and quasi-resonant controller-based ADRC (QRC-ADRC) under both steady-state and dynamic conditions. Full article

While DC/DC converters for water electrolysis systems have been widely investigated, they inherently face a critical compromise between wide voltage regulation capabilities and dynamic response characteristics. This study is based on a two-stage hybrid topology (TSIB-TPLLC) that synergistically combines a two-phase interleaved buck converter with a three-phase LLC resonant converter to resolve this challenge. The first-stage interleaved buck converter enables wide-range voltage regulation while reducing input current ripple and minimizing intermediate bus capacitance through phase-interleaved operation. The subsequent three-phase LLC stage operates at a fixed resonant frequency, achieving inherent output current ripple suppression through multi-phase cancellation while maintaining high conversion efficiency. A dual-loop control architecture incorporating linear active disturbance rejection control (LADRC) with PI compensation is developed to improve transient response compared to conventional PI-based methods. Finally, a 1.2 kW experimental prototype with an input voltage of 250 V and an output voltage of 24 V demonstrates the converter’s operational feasibility and enhanced steady-state/transient performance, confirming its suitability for hydrogen production applications. Full article