Search Results (210)

Permanent magnet synchronous machines (PMSMs) are widely used in high-performance drive systems. However, parasitic torque ripple remains a critical limitation, causing acoustic noise, mechanical vibration, and speed fluctuations. This study presents a compact, model-based torque control strategy for surface-mounted PMSMs (SPMSMs) that suppresses torque ripple by generating a structured current reference. Grounded in the magnetic co-energy principle, the proposed method utilizes a deterministic analytical model to compensate for cogging torque and inductance harmonics, avoiding computationally intensive iterative estimators. A primary contribution involves adapting the harmonic injection profile to varying loads and magnetic saturation levels. Comprehensive finite element analysis (FEA) co-simulations demonstrate that the proposed method reduces torque ripple by approximately 87.5% and speed ripple by over 90% at 1500 RPM compared to conventional maximum torque per ampere (MTPA) strategies. Furthermore, extended dynamic analysis confirms superior robustness during start-up, transients, and low-speed operation (100 RPM), maintaining high control authority even under deep magnetic saturation (2.0 p.u.). Performance evaluations verify that this significant enhancement in torque quality is achieved with a negligible increase in total power losses (~2.1%), presenting a computationally feasible solution for industrial embedded platforms. Full article

Existing model predictive control (MPC) schemes based on virtual voltage vectors (VVVs) for dual three-phase permanent magnet synchronous motors (DT-PMSMs) typically employ a limited set of voltage vectors, which restricts further improvement in steady-state performance. Moreover, the design of switching sequences lacks systematic consideration, focusing mainly on harmonic current suppression while neglecting practical engineering challenges associated with software-layer implementation. This paper proposes an optimized model predictive torque control (MPTC) method for DT-PMSMs using an expanded voltage vector set. First, to enhance steady-state performance, an extended control set of voltage vectors is designed, which introduces not only new directions but also two distinct voltage amplitude levels, resulting in a total of 48 voltage vectors. Second, to alleviate the significant computational burden caused by traversing the extended set for prediction, a candidate voltage vector selection table is constructed based on the sector position of the stator flux linkage and the requirements for torque and flux adjustment. This approach reduces the computational load to only 10 predictive calculations per control cycle, avoiding exhaustive traversal of the extended set. Furthermore, for all VVVs in the control set, a switching sequence combining active voltage vectors with zero vectors is designed to facilitate straightforward digital implementation. Finally, experimental results are provided to validate the effectiveness of the proposed method. Full article

White Mustard (Sinapis alba) seeds contain glucosinolates, mainly sinigrin and sinalbin. Isothiocyanate metabolites, together with flavonoids and tocopherols, present anti-inflammatory, antimicrobial, and antioxidant activities. This narrative review is a result of a literature search in PubMed, Scopus, and Google Scholar, spanning in vitro, in vivo. and clinical studies. The presented data highlight that mustard-derived products suppress pro-inflammatory cytokines such as TNF-α and inhibit a broad spectrum of pathogens at micromolar concentrations. In the largest (n = 113) double-blind dental trial to date, a white-mustard toothpaste reduced the mean value of Silness-Löe plaque index by −2.43 vs. −1.95 placebo and bleeding on probing by 30.6% vs. 26.8% within four weeks, while salivary Streptococcus mutans and Porphyromonas gingival colony counts decreased by 40%. A six-month follow-up study with a sinigrin-rich “Bamberka” extract confirmed these gains and selectively suppressed red-complex periopathogens. Clinical translation is limited by heterogeneous extraction methods, a lack of phytochemical standardization, and an unresolved allergenic risk linked to seed proteins Sin a 1 and Sin a 2. Mustard, therefore, emerges as a promising phytotherapeutic adjunct for controlling inflammation, infection, and oxidative stress, but widespread use awaits harmonized manufacturing guidelines, comprehensive allergological screening, and rigorously designed randomized trials benchmarked against chlorhexidine. Full article

To address the low-voltage fault issue in doubly fed induction generator-motor (DFIGM) systems, this paper proposes a practically implementable cooperative control strategy that integrates an improved current reversely tracking control (CRTC) scheme with an enhanced IGBT-based active crowbar topology. The proposed method optimizes the current-tracking coefficients under rotor voltage and current constraints during LVRT operation. Meanwhile, the enhanced active crowbar provides reactive power support, thereby suppressing negative-sequence current components, mitigating harmonic distortion, and improving the power quality at the point of common coupling (PCC). A 10-MW DFIGM model is developed, and comparative studies are conducted with the conventional inductance emulating control (IEC) and the crowbar structure. The experimental results show the feasibility and effectiveness of the proposed method. Full article

Harmonic resonance challenges have intensified in modern power grids, primarily due to the high penetration of converter-based offshore wind energy. Traditional modal analysis methods conducted in the abc reference frame are often constrained by complex coordinate transformations and laborious analytical procedures. Therefore, research into dq-domain modal analysis and mitigation techniques is essential. This paper first elucidates the limitations of conventional modal analysis and outlines the fundamental principles of the dq-domain approach, validating its effectiveness through a three-bus test system. Subsequently, a resonance analysis model for offshore wind systems is established to derive the complete nodal admittance matrix. A dq-domain resonance analysis is then performed, and resonance is mitigated by optimizing the control parameters. Finally, the proposed dq-domain modal analysis method and suppression strategy are validated using a laboratory-scale experimental testbed. The results indicate that the proportional gain of the power control loop (K_PP) significantly influences the system’s resonance modes. Fine-tuning controller parameters via modal analysis provides an active, flexible, and cost-effective solution for resonance suppression. Full article

To meet the demand for high efficiency in modern broadband communication systems, this paper presents a novel continuous-mode Doherty power amplifier design method based on integrated high-order filter prototypes. By deeply merging the filter structure with the output matching network, broadband impedance transformation and harmonic suppression are simultaneously achieved within the 1.6–2.2 GHz frequency range. This approach resolves the bandwidth limitations and efficiency degradation caused by the conventional separation of matching and harmonic control stages. Using a CGH40010F GaN transistor, the impedance space was determined through load-pull analysis, and the design flexibility was enhanced by applying continuous Class-F mode theory. The implemented amplifier demonstrates a saturated efficiency of 68–72%, a 6 dB back-off efficiency of 58.9–64.9%, a saturated output power exceeding 45 dBm, an in-band gain greater than 11.2 dB, and a return loss better than −15 dB. The proposed method offers an effective solution for the design of high-performance broadband power amplifiers. Full article

The stochastic fluctuations of AI computational loads inject harmonic currents into the DC bus, amplifying bus voltage ripples and weakening the power quality. Existing strategies typically rely on high-gain control strategies to minimize harmonic output impedance, aiming at full absorption of harmonic currents. However, such designs rarely consider engineering constraints such as capacity and current boundaries, which impose inherent limits on harmonic absorption. To address these issues, this paper proposes an adaptive harmonic impedance control and flexible compensation method for AI data centers. By integrating DC bus voltage feedforward with output current feedback, a virtual harmonic impedance control channel is constructed to enable real-time impedance shaping. Then, an adaptive gain regulation mechanism is developed to adjust harmonic impedance according to the available capacity and current margin. Compared with traditional strategies relying on fixed high gains or resonant links, the proposed method allows for the continuous regulation of harmonic impedance over a wide range. This enables the dynamic matching of harmonic absorption capability with the available capacity, effectively suppressing the risks of overcurrent, saturation, and stability degradation. Simulation and 8 kW experimental results verify the correctness and effectiveness of the proposed analysis and control strategy. Full article

The rapid growth of electric vehicle (EV) deployment has created a strong demand for charging systems capable of handling higher power levels while preserving grid stability and maintaining satisfactory energy quality. In this work, a fast-charging architecture for 400 V battery systems is developed using a Vienna rectifier on the AC front end and a DC–DC buck converter on the DC stage. To enhance the performance of this topology, two complementary control techniques are combined: the Crystal Structure Algorithm (CryStAl), used for offline optimization of switching behavior, and a Random Decision Forest (RDF) model, employed for real-time adaptation to operating conditions. A clear, step-oriented derivation of the converter state–space equations is included to support controller design and ensure reproducibility. This control framework improves the key performance indices, including Total Harmonic Distortion (THD), ripple suppression, efficiency, and power factor correction. Specifically, the Vienna rectifier works on input current shaping and enhances the power quality, while the buck converter maintains a constant DC output appropriate for reliable battery charging. The simulation studies show that the combined CryStAl–RDF approach outperforms the conventional PI- and Particle Swarm Optimization (PSO)-based controllers. The proposed method achieves THD less than 2%, conversion efficiency higher than 97.5%, and a power factor close to unity. The voltage and current ripples are also significantly reduced, which justifies the extended life of the batteries and reliable charging performance. Overall, the results portray the potential of the combined metaheuristic optimization with machine learning-based decision techniques to enhance the behavior of power electronic converters for EV fast-charging applications. The proposed control method offers a practical and scalable route for next-generation EV charging infrastructure. Full article

Large-scale grid integration of renewable generation is facilitated by resource abundance and advancements in power electronics. The high penetration of power electronics-based devices reduces system inertia, threatening grid stability. The Virtual Synchronous Generator (VSG) provides an effective solution. However, when the grid is unbalanced, problems such as unbalanced output current, overcurrent, and power fluctuations occur. Thus, a VSG power–current collaborative control strategy based on improved second-order generalized integrator (SOGI) is proposed. Firstly, the generation of power fluctuation and unbalanced current in VSG output under an unbalanced power grid is analyzed. Secondly, to suppress the DC component and high-order harmonics, an improved SOGI method is proposed for positive and negative sequence separation by introducing a difference node and adding an extra SOGI module on the basis of the traditional SOGI. To achieve the collaborative control of active/reactive power constant and current balance, a correlation coefficient μ is introduced and a unified equation is constructed. To prevent overcurrent during fault, virtual impedance and reactive power reference are introduced. Simulations have verified the effectiveness of the proposed method. It shows superiority in effective sequence separation, smooth power–current collaborative control, and safe operation without overcurrent. Full article

Vibration is a critical issue in aerospace structures, where lightweight design, high flexibility, and complex operational environments often lead to pronounced nonlinear dynamic responses. Excessive vibrations induced by harmonic excitations, aerodynamic loads, or onboard equipment can significantly degrade structural integrity, control accuracy, and service life. Consequently, advanced passive vibration suppression techniques with strong robustness and broadband effectiveness are of great importance in aerospace engineering applications. The bifurcation boundary and vibration suppression performance of Piezoelectric–Monostable Nonlinear Energy Sink (PMNES) are crucial for evaluating its effectiveness on the main structure. To simplify the analysis of flexible aerospace structures, a reduced-order model is derived by modal truncation in the low-frequency range, which is then treated as a two-degree-of-freedom main structure. To focus on the underlying nonlinear dynamic mechanisms, an equivalent two-degree-of-freedom lumped-parameter system is adopted as a generic representation of the dominant low-frequency dynamics of flexible aerospace structures. In this work, the electromechanical coupling control equations of the system of a two-degree-of-freedom main structure coupled with PNES are derived through the application of Newton’s second law and Kirchhoff’s voltage law. The methods of complexification-averaging (CX-A) and Runge–Kutta (RK) are employed to assess the vibration suppression performance and stability characteristics of the system under harmonic excitation. The approximate solution is validated through numerical solutions. The approximate solutions of the system are employed to derive the Saddle Node (SN) bifurcation and codimension-two cusp bifurcation points, while the enhanced algorithm is employed to ascertain the most unfavorable amplitude at each external excitation circular frequency and to determine whether the mark represents a Hopf Bifurcation (HB) point. The generalized transmissibility is utilized to assess the efficacy of vibration suppression. The various vibration suppression efficiency regions are created by superimposing the vibration suppression efficiency maps and bifurcation maps. The influence of PNES parameters on the vibration suppression region is investigated. The results indicate that this method can effectively evaluate the bifurcation boundary and vibration suppression performance of PMNES. Full article

Exercise-induced myokines have emerged as crucial mediators of the beneficial effects of physical activity on neurodegenerative diseases through complex molecular mechanisms involving oxidative stress reduction, neuroinflammation suppression, and synaptic plasticity enhancement. Among these myokines, irisin, encoded by the FNDC5 gene, has gained significant attention as a potential therapeutic target in neurodegenerative conditions due to its ability to cross the blood–brain barrier and exert pleiotropic neuroprotective effects. This review synthesizes current evidence from both preclinical and clinical studies examining the role of exercise-induced irisin in neurodegeneration, with particular emphasis on translational potential and therapeutic applications. A comprehensive search was conducted across PubMed, Web of Science, Scopus, and EMBASE databases (spanning January 2015 to December 2024) to identify peer-reviewed articles investigating irisin’s neuroprotective mechanisms in neurodegenerative diseases. Ten studies met the inclusion criteria (five rodent/primate model studies and five human clinical investigations), which were analyzed for methodological rigor, intervention protocols, biomarker quantification methods, and reported outcomes. Reviewed studies consistently demonstrated that exercise-induced endogenous irisin elevation correlates with improved cognitive function, reduced neuroinflammatory markers, enhanced synaptic plasticity, and modulation of neurodegenerative pathways, with exogenous irisin administration reproducing several neuroprotective benefits observed with exercise training in animal models. However, substantial heterogeneity exists regarding exercise prescription parameters (intensity, duration, frequency, modality), training-induced irisin quantification methodologies (ELISA versus mass spectrometry), and study designs (ranging from uncontrolled human observations to randomized controlled trials in animal models). Critical appraisal reveals that human studies lack adequate control for confounding variables including baseline physical fitness, comorbidities, concurrent medications, and potential sources of bias, while biochemical studies indicate distinct pharmacokinetics between endogenous training-induced irisin and exogenous bolus dosing, necessitating careful interpretation of therapeutic applicability. The translational potential of irisin as a therapeutic agent or drug target depends on resolving methodological standardization in biomarker measurement, conducting well-designed clinical trials with rigorous control for confounders, and integrating findings from molecular/biochemical studies to elucidate mechanisms linking irisin to disease modification. Future research should prioritize establishing clinical trial frameworks that harmonize exercise prescriptions, employ robust biomarker quantification (mass spectrometry), and stratify participants based on disease stage, comorbidities, and genetic predisposition to clarify irisin’s role as a potential therapeutic intervention in neurodegenerative disease management. Full article

With the advancement of power electronics technology, converters achieve compactness and high power density by increasing switching frequency and reducing passive components. However, this compromises the filtering capability to suppress high-frequency harmonics and intensifies high-frequency resonance issues in multi-machine interconnected systems. The problem becomes even more complex in grid-following (GFL) and grid-forming (GFM) converter interconnected systems due to their distinct dynamic characteristics. Traditional active damping methods fail to effectively mitigate such high-frequency resonances. For GFL converters, this paper investigates the interaction mechanisms between various active damping techniques and high-frequency harmonics, and proposes a virtual-filter-based active damping method that feeds back capacitor voltage through a quasi-resonant controller. This approach effectively suppresses high-frequency resonance, maintains high control bandwidth, and avoids the drawback of conventional capacitor-voltage feedforward, which tends to amplify high-frequency disturbances. For GFL-GFM interconnected systems, the paper further analyzes how different active damping strategies affect system damping characteristics and the interaction between GFL and GFM converters, leading to a rational active damping configuration. The proposed scheme successfully suppresses high-frequency resonance while preserving fast dynamic response, with experimental results confirming its effectiveness and feasibility. Full article

To address the torque ripple and speed fluctuation issues in high-frequency square-wave injection-based sensorless control of interior permanent magnet synchronous motors (IPMSM) caused by low-order stator current harmonics (primarily the fifth and seventh), this paper proposes a harmonic voltage compensation strategy based on a sixth-order quasi-proportional resonant (QPR) controller, which effectively suppresses these specific harmonic disturbances. The proposed method, building upon conventional high-frequency square-wave injection, introduces a harmonic current extraction technique based on multiple synchronous reference frame transformations to separate the fifth and seventh harmonic components accurately; then, according to the established harmonic voltage compensation equation, generates targeted compensation voltage commands; finally, further precisely suppresses the corresponding harmonic currents through a sixth-order QPR controller connected in parallel with the current proportional-integral (PI) controller. This paper comprehensively establishes the mathematical models for harmonic extraction and voltage compensation, and conducts a detailed analysis of the parameter design of the sixth-order QPR controller. Simulation results demonstrate that the proposed strategy can significantly suppress stator current distortion, effectively reduce torque and speed ripples, and substantially improve rotor position estimation accuracy, thereby verifying the superiority of the novel harmonic-suppression-based sensorless control strategy. Full article

Grid-forming power converters play a foundational role in modern microgrids and inverter-dominated distribution systems by establishing voltage and frequency references during islanded or low-inertia operation. However, when subjected to nonlinear or impulsive impact-type loads, these converters often suffer from severe harmonic distortion and transient current overshoot, leading to waveform degradation and protection-triggered failures. While virtual impedance control has been widely adopted to mitigate these issues, conventional implementations rely on fixed or rule-based tuning heuristics that lack adaptivity and robustness under dynamic, uncertain conditions. This paper proposes a novel reinforcement learning-based framework for real-time virtual impedance scheduling in grid-forming converters, enabling simultaneous optimization of harmonic suppression and impact load resilience. The core of the methodology is a Soft Actor-Critic (SAC) agent that continuously adjusts the converter’s virtual impedance tensor—comprising dynamically tunable resistive, inductive, and capacitive elements—based on real-time observations of voltage harmonics, current derivatives, and historical impedance states. A physics-informed simulation environment is constructed, including nonlinear load models with dominant low-order harmonics and stochastic impact events emulating asynchronous motor startups. The system dynamics are modeled through a high-order nonlinear framework with embedded constraints on impedance smoothness, stability margins, and THD compliance. Extensive training and evaluation demonstrate that the learned impedance policy effectively reduces output voltage total harmonic distortion from over 8% to below 3.5%, while simultaneously limiting current overshoot during impact events by more than 60% compared to baseline methods. The learned controller adapts continuously without requiring explicit load classification or mode switching, and achieves strong generalization across unseen operating conditions. Pareto analysis further reveals the multi-objective trade-offs learned by the agent between waveform quality and transient mitigation. Full article

Under unbalanced grid conditions, the three-phase Vienna rectifier exhibits significant voltage fluctuations in dc-link and asymmetric input currents. Traditional control methods cannot simultaneously suppress the voltage ripples in dc-link and balance the input currents. Therefore, a weighted control strategy based on the degree of current imbalance is proposed in this paper. The strategy is implemented within a dual closed-loop architecture, featuring a finite-set model predictive control (FS-MPC) method in the current loop and a sliding mode control (SMC) method in the voltage loop. In the current loop, the two control objectives of voltage in dc-link and input current are weighted, and the weighting factor is dynamically adjusted based on the degree of current imbalance. This strategy can simultaneously achieve control for input current symmetry and dc-link voltage balance under unbalanced grid conditions. Finally, a 2 kW Vienna rectifier experimental platform was independently constructed. Simulation and experimental results indicate that under unbalanced grid conditions, the proposed control strategy achieves approximately 10% lower total harmonic distortion (THD) and maintains DC-link voltage fluctuation within 5 V, compared to traditional control methods. Full article