Transient Damping of Virtual Synchronous Generator for Enhancing Synchronization Stability during Voltage Dips

Virtual synchronous generators(VSGs)are widely introduced to the renewable power generation,the variablespeed pumped storage units,and so on,as a promising gridforming solution.It is noted that VSGs can provide virtual inertia for frequency support,but the larger inertia would worsen the synchronization stability,referring to keeping synchronization with the grid during voltage dips.Thus,this paper presents a transient damping method of VSGs for enhancing the synchronization stability during voltage dips.It is revealed that the loss of synchronization(LOS)of VSGs always accompanies with the positive frequency deviation and the damping is the key factor to remove LOS when the equilibrium point exists.In order to enhance synchronization stability during voltage dips,the transient damping is proposed,which is generated by the frequency deviation in active power loop.Additionally,the proposed method can realize seamless switching between normal state and grid fault.Moreover,detailed control design for transient damping gain is given to ensure the synchronization stability under different inertia requirements during voltage dips.Finally,the experimental results are presented to validate the analysis and the effectiveness of the improved transient damping method.

Synchronous gastric and colon cancers:Important to consider hereditary syndromes and chronic inflammatory disease associations

In this editorial we comment on the manuscript,describing management and surveillance strategies in synchronous and metachronous,gastric and colon cancers.Synchronous or metachronous primary malignancies at different sites of the gastrointestinal tract pose a unique diagnostic and therapeutic challenge.Multidisciplinary services and strategies are required for the management of multiple site primary malignancies,to provide the best oncological outcomes.Although this study highlights the dual cancers in 76 sporadic cases,the authors excluded 55 patients due to combination of factors which includes;incomplete clinical data,genetic syndrome,gastric stump cancers.In addition,the authors did not elaborate if any patients presented with signet ring cell morphology,E-cadherin mutations or presence of inflammatory bowel disease.Genetic and mutational errors and epithelial field defects from chronic inflammatory diseases of the gastrointestinal tract are important when considering synchronous gastric and colonic cancers.We will briefly discuss these in this editorial.

Analysis and Research on Mechanical Stress and Multiobjective Optimization of Synchronous Reluctance Motor

The mechanical strength of the synchronous reluctance motor(SynRM)has always been a great challenge.This paper presents an analysis method for assessing stress equivalence and magnetic bridge stress interaction,along with a multiobjective optimization approach.Considering the complex flux barrier structure and inevitable stress concentration at the bridge,the finite element model suitable for SynRM is established.Initially,a neural network structure with two inputs,one output,and three layers is established.Continuous functions are constructed to enhance accuracy.Additionally,the equivalent stress can be converted into a contour distribution of a three-dimensional stress graph.The contour line distribution illustrates the matching scheme for magnetic bridge lengths under equivalent stress.Moreover,the paper explores the analysis of magnetic bridge interaction stress.The optimization levels corresponding to the length of each magnetic bridge are defined,and each level is analyzed by the finite element method.The Taguchi method is used to determine the specific gravity of the stress source on each magnetic bridge.Based on this,a multiobjective optimization employing the Multiobjective Particle Swarm Optimization(MOPSO)technique is introduced.By taking the rotor magnetic bridge as the design parameter,ten optimization objectives including air-gap flux density,sinusoidal property,average torque,torque ripple,and mechanical stress are optimized.The relationship between the optimization objectives and the design parameters can be obtained based on the response surface method(RSM)to avoid too many experimental samples.The optimized model is compared with the initial model,and the optimized effect is verified.Finally,the temperature distribution of under rated working conditions is analyzed,providing support for addressing thermal stress as mentioned earlier.

Improved Particle Swarm Optimization for Parameter Identification of Permanent Magnet Synchronous Motor

In the process of identifying parameters for a permanent magnet synchronous motor,the particle swarm optimization method is prone to being stuck in local optima in the later stages of iteration,resulting in low parameter accuracy.This work proposes a fuzzy particle swarm optimization approach based on the transformation function and the filled function.This approach addresses the topic of particle swarmoptimization in parameter identification from two perspectives.Firstly,the algorithm uses a transformation function to change the form of the fitness function without changing the position of the extreme point of the fitness function,making the extreme point of the fitness function more prominent and improving the algorithm’s search ability while reducing the algorithm’s computational burden.Secondly,on the basis of themulti-loop fuzzy control systembased onmultiplemembership functions,it is merged with the filled function to improve the algorithm’s capacity to skip out of the local optimal solution.This approach can be used to identify the parameters of permanent magnet synchronous motors by sampling only the stator current,voltage,and speed data.The simulation results show that the method can effectively identify the electrical parameters of a permanent magnet synchronous motor,and it has superior global convergence performance and robustness.

Localization method of subsynchronous oscillation source based on high-resolution time-frequency distribution image and CNN

The penetration of new energy sources such as wind power is increasing,which consequently increases the occurrence rate of subsynchronous oscillation events.However,existing subsynchronous oscillation source-identification methods primarily analyze fixed-mode oscillations and rarely consider time-varying features,such as frequency drift,caused by the random volatility of wind farms when oscillations occur.This paper proposes a subsynchronous oscillation sourcelocalization method that involves an enhanced short-time Fourier transform and a convolutional neural network(CNN).First,an enhanced STFT is performed to secure high-resolution time-frequency distribution(TFD)images from the measured data of the generation unit ports.Next,these TFD images are amalgamated to form a subsynchronous oscillation feature map that serves as input to the CNN to train the localization model.Ultimately,the trained CNN model realizes the online localization of subsynchronous oscillation sources.The effectiveness and accuracy of the proposed method are validated via multimachine system models simulating forced and natural oscillation events using the Power Systems Computer Aided Design platform.Test results show that the proposed method can localize subsynchronous oscillation sources online while considering unpredictable fluctuations in wind farms,thus providing a foundation for oscillation suppression in practical engineering scenarios.

Review of Field Weakening Control Strategies of Permanent Magnet Synchronous Motors

Due to high power density,high efficiency,and accurate control performance,permanent magnet synchronous motors(PMSMs)have been widely adopted in equipment manufacturing and energy transformation fields.To expand the speed range under finite DC-bus voltage,extensive research on field weakening(FW)control strategies has been conducted.This paper summarizes the major FW control strategies of PMSMs,which are categorized into calculation-based methods,voltage closed-loop control methods,and model predictive control related methods.The existing strategies are analyzed and compared according to performance,robustness,and execution difficulty,which can facilitate the implementation of FW control.

Disturbances rejection optimization based on improved two-degree-of-freedom LADRC for permanent magnet synchronous motor systems

Permanent magnet synchronous motor(PMSM)speed control systems with conventional linear active disturbance rejection control(CLADRC)strategy encounter issues regarding the coupling between dynamic response and disturbance suppression and have poor performance in suppressing complex nonlinear disturbances.In order to address these issues,this paper proposes an improved two-degree-of-freedom LADRC(TDOF-LADRC)strategy,which can enhance the disturbance rejection performance of the system while decoupling entirely the system's dynamic and anti-disturbance performance to boost the system robustness and simplify controller parameter tuning.PMSM models that consider total disturbances are developed to design the TDOF-LADRC speed controller accurately.Moreover,to evaluate the control performance of the TDOF-LADRC strategy,its stability is proven,and the influence of each controller parameter on the system control performance is analyzed.Based on it,a comparison is made between the disturbance observation ability and anti-disturbance performance of TDOF-LADRC and CLADRC to prove the superiority of TDOF-LADRC in rejecting disturbances.Finally,experiments are performed on a 750 W PMSM experimental platform,and the results demonstrate that the proposed TDOF-LADRC exhibits the properties of two degrees of freedom and improves the disturbance rejection performance of the PMSM system.

Machine learning prediction model for gray-level co-occurrence matrix features of synchronous liver metastasis in colorectal cancer

BACKGROUND Synchronous liver metastasis(SLM)is a significant contributor to morbidity in colorectal cancer(CRC).There are no effective predictive device integration algorithms to predict adverse SLM events during the diagnosis of CRC.AIM To explore the risk factors for SLM in CRC and construct a visual prediction model based on gray-level co-occurrence matrix(GLCM)features collected from magnetic resonance imaging(MRI).METHODS Our study retrospectively enrolled 392 patients with CRC from Yichang Central People’s Hospital from January 2015 to May 2023.Patients were randomly divided into a training and validation group(3:7).The clinical parameters and GLCM features extracted from MRI were included as candidate variables.The prediction model was constructed using a generalized linear regression model,random forest model(RFM),and artificial neural network model.Receiver operating characteristic curves and decision curves were used to evaluate the prediction model.RESULTS Among the 392 patients,48 had SLM(12.24%).We obtained fourteen GLCM imaging data for variable screening of SLM prediction models.Inverse difference,mean sum,sum entropy,sum variance,sum of squares,energy,and difference variance were listed as candidate variables,and the prediction efficiency(area under the curve)of the subsequent RFM in the training set and internal validation set was 0.917[95%confidence interval(95%CI):0.866-0.968]and 0.09(95%CI:0.858-0.960),respectively.CONCLUSION A predictive model combining GLCM image features with machine learning can predict SLM in CRC.This model can assist clinicians in making timely and personalized clinical decisions.

Five-phase Synchronous Reluctance Machines Equipped with a Novel Type of Fractional Slot Winding

Multi-phase machines are so attractive for electrical machine designers because of their valuable advantages such as high reliability and fault tolerant ability.Meanwhile,fractional slot concentrated windings(FSCW)are well known because of short end winding length,simple structure,field weakening sufficiency,fault tolerant capability and higher slot fill factor.The five-phase machines equipped with FSCW,are very good candidates for the purpose of designing motors for high reliable applications,like electric cars,major transporting buses,high speed trains and massive trucks.But,in comparison to the general distributed windings,the FSCWs contain high magnetomotive force(MMF)space harmonic contents,which cause unwanted effects on the machine ability,such as localized iron saturation and core losses.This manuscript introduces several new five-phase fractional slot winding layouts,by the means of slot shifting concept in order to design the new types of synchronous reluctance motors(SynRels).In order to examine the proposed winding’s performances,three sample machines are designed as case studies,and analytical study and finite element analysis(FEA)is used for validation.

An Adaptive Control Strategy for Energy Storage Interface Converter Based on Analogous Virtual Synchronous Generator

In the DC microgrid,the lack of inertia and damping in power electronic converters results in poor stability of DC bus voltage and low inertia of the DC microgrid during fluctuations in load and photovoltaic power.To address this issue,the application of a virtual synchronous generator(VSG)in grid-connected inverters control is referenced and proposes a control strategy called the analogous virtual synchronous generator(AVSG)control strategy for the interface DC/DC converter of the battery in the microgrid.Besides,a flexible parameter adaptive control method is introduced to further enhance the inertial behavior of the AVSG control.Firstly,a theoretical analysis is conducted on the various components of the DC microgrid,the structure of analogous virtual synchronous generator,and the control structure’s main parameters related to the DC microgrid’s inertial behavior.Secondly,the voltage change rate tracking coefficient is introduced to adjust the change of the virtual capacitance and damping coefficient flexibility,which further strengthens the inertia trend of the DC microgrid.Additionally,a small-signal modeling approach is used to analyze the approximate range of the AVSG’s main parameters ensuring system stability.Finally,conduct a simulation analysis by building the model of the DC microgrid system with photovoltaic(PV)and battery energy storage(BES)in MATLAB/Simulink.Simulation results from different scenarios have verified that the AVSG control introduces fixed inertia and damping into the droop control of the battery,resulting in a certain level of inertia enhancement.Furthermore,the additional adaptive control strategy built upon the AVSG control provides better and flexible inertial support for the DC microgrid,further enhances the stability of the DC bus voltage,and has a more positive impact on the battery performance.

Cascaded ELM-Based Joint Frame Synchronization and Channel Estimation over Rician Fading Channel with Hardware Imperfections

Due to the interdependency of frame synchronization(FS)and channel estimation(CE),joint FS and CE(JFSCE)schemes are proposed to enhance their functionalities and therefore boost the overall performance of wireless communication systems.Although traditional JFSCE schemes alleviate the influence between FS and CE,they show deficiencies in dealing with hardware imperfection(HI)and deterministic line-of-sight(LOS)path.To tackle this challenge,we proposed a cascaded ELM-based JFSCE to alleviate the influence of HI in the scenario of the Rician fading channel.Specifically,the conventional JFSCE method is first employed to extract the initial features,and thus forms the non-Neural Network(NN)solutions for FS and CE,respectively.Then,the ELMbased networks,named FS-NET and CE-NET,are cascaded to capture the NN solutions of FS and CE.Simulation and analysis results show that,compared with the conventional JFSCE methods,the proposed cascaded ELM-based JFSCE significantly reduces the error probability of FS and the normalized mean square error(NMSE)of CE,even against the impacts of parameter variations.

Dynamics and synchronization of neural models with memristive membranes under energy coupling

Dynamical modeling of neural systems plays an important role in explaining and predicting some features of biophysical mechanisms.The electrophysiological environment inside and outside of the nerve cell is different.Due to the continuous and periodical properties of electromagnetic fields in the cell during its operation,electronic components involving two capacitors and a memristor are effective in mimicking these physical features.In this paper,a neural circuit is reconstructed by two capacitors connected by a memristor with periodical mem-conductance.It is found that the memristive neural circuit can present abundant firing patterns without stimulus.The Hamilton energy function is deduced using the Helmholtz theorem.Further,a neuronal network consisting of memristive neurons is proposed by introducing energy coupling.The controllability and flexibility of parameters give the model the ability to describe the dynamics and synchronization behavior of the system.

MEMS Huygens Clock Based on Synchronized Micromechanical Resonators

With the continuous miniaturization of electronic devices,microelectromechanical system(MEMS)oscillators that can be combined with integrated circuits have attracted increasing attention.This study reports a MEMS Huygens clock based on the synchronization principle,comprising two synchronized MEMS oscillators and a frequency compensation system.The MEMS Huygens clock improved shorttime stability,improving the Allan deviation by a factor of 3.73 from 19.3 to 5.17 ppb at 1 s.A frequency compensation system based on the MEMS oscillator’s temperature-frequency characteristics was developed to compensate for the frequency shift of the MEMS Huygens clock by controlling the resonator current.This effectively improved the long-term stability of the oscillator,with the Allan deviation improving by 1.6343105 times to 30.9 ppt at 6000 s.The power consumption for compensating both oscillators simultaneously is only 2.85 mW·℃^(-1).Our comprehensive solution scheme provides a novel and precise engineering solution for achieving high-precision MEMS oscillators and extends synchronization applications in MEMS.

A frequency domain estimation and compensation method for system synchronization parameters of distributed-HFSWR

To analyze the influence of time synchronization error,phase synchronization error,frequency synchronization error,internal delay of the transceiver system,and range error and angle error between the unit radars on the target detection performance,firstly,a spatial detection model of distributed high-frequency surface wave radar(distributed-HFSWR)is established in this paper.In this model,a method for accurate extraction of direct wave spectrum based on curve fitting is proposed to obtain accurate system internal delay and frequency synchronization error under complex electromagnetic environment background and low signal to noise ratio(SNR),and to compensate for the shift of range and Doppler frequency caused by time-frequency synchronization error.The direct wave component is extracted from the spectrum,the range estimation error and Doppler estimation error are reduced by the method of curve fitting,and the fitting accuracy of the parameters is improved.Then,the influence of frequency synchronization error on target range and radial Doppler velocity is quantitatively analyzed.The relationship between frequency synchronization error and radial Doppler velocity shift and range shift is given.Finally,the system synchronization parameters of the trial distributed-HFSWR are obtained by the proposed spectrum extraction method based on curve fitting,the experimental data is compensated to correct the shift of the target,and finally the correct target parameter information is obtained.Simulations and experimental results demonstrate the superiority and correctness of the proposed method,theoretical derivation and detection model proposed in this paper.

Synchronization and firing mode transition of two neurons in a bilateral auditory system driven by a high–low frequency signal

The FitzHugh–Nagumo neuron circuit integrates a piezoelectric ceramic to form a piezoelectric sensing neuron,which can capture external sound signals and simulate the auditory neuron system.Two piezoelectric sensing neurons are coupled by a parallel circuit consisting of a Josephson junction and a linear resistor,and a binaural auditory system is established.Considering the non-singleness of external sound sources,the high–low frequency signal is used as the input signal to study the firing mode transition and synchronization of this system.It is found that the angular frequency of the high–low frequency signal is a key factor in determining whether the dynamic behaviors of two coupled neurons are synchronous.When they are in synchronization at a specific angular frequency,the changes in physical parameters of the input signal and the coupling strength between them will not destroy their synchronization.In addition,the firing mode of two coupled auditory neurons in synchronization is affected by the characteristic parameters of the high–low frequency signal rather than the coupling strength.The asynchronous dynamic behavior and variations in firing modes will harm the auditory system.These findings could help determine the causes of hearing loss and devise functional assistive devices for patients.

Quantum synchronization with correlated baths

We study quantum synchronization under the nonequilibrium reservoirs.We consider a two-qubit XXZ chain coupled independently to their own reservoirs modeled by the collisional model.Two reservoir particles,initially prepared in a thermal state or a state with coherence,are correlated through a unitary transformation and afterward interact locally with the two quantum subsystems.We study the quantum effect of reservoir on synchronous dynamics of system.By preparing different reservoir initial states or manipulating the reservoir particles coupling and the temperature gradient,we find that quantum entanglement of reservoir is the key to control quantum synchronization of system qubits.

A Synchronization Acquisition Algorithm Based on the Frequency Hopping Pulses Combining

As modern electromagnetic environments are more and more complex,the anti-interference performance of the synchronization acquisition is becoming vital in wireless communications.With the rapid development of the digital signal processing technologies,some synchronization acquisition algorithms for hybrid direct-sequence(DS)/frequency hopping(FH)spread spectrum communications have been proposed.However,these algorithms do not focus on the analysis and the design of the synchronization acquisition under typical interferences.In this paper,a synchronization acquisition algorithm based on the frequency hopping pulses combining(FHPC)is proposed.Specifically,the proposed algorithm is composed of two modules:an adaptive interference suppression(IS)module and an adaptive combining decision module.The adaptive IS module mitigates the effect of the interfered samples in the time-domain or the frequencydomain,and the adaptive combining decision module can utilize each frequency hopping pulse to construct an anti-interference decision metric and generate an adaptive acquisition decision threshold to complete the acquisition.Theory and simulation demonstrate that the proposed algorithm significantly enhances the antiinterference and anti-noise performances of the synchronization acquisition for hybrid DS/FH communications.

Dynamics and synchronization in a memristor-coupled discrete heterogeneous neuron network considering noise

Research on discrete memristor-based neural networks has received much attention.However,current research mainly focuses on memristor–based discrete homogeneous neuron networks,while memristor-coupled discrete heterogeneous neuron networks are rarely reported.In this study,a new four-stable discrete locally active memristor is proposed and its nonvolatile and locally active properties are verified by its power-off plot and DC V–I diagram.Based on two-dimensional(2D)discrete Izhikevich neuron and 2D discrete Chialvo neuron,a heterogeneous discrete neuron network is constructed by using the proposed discrete memristor as a coupling synapse connecting the two heterogeneous neurons.Considering the coupling strength as the control parameter,chaotic firing,periodic firing,and hyperchaotic firing patterns are revealed.In particular,multiple coexisting firing patterns are observed,which are induced by different initial values of the memristor.Phase synchronization between the two heterogeneous neurons is discussed and it is found that they can achieve perfect synchronous at large coupling strength.Furthermore,the effect of Gaussian white noise on synchronization behaviors is also explored.We demonstrate that the presence of noise not only leads to the transition of firing patterns,but also achieves the phase synchronization between two heterogeneous neurons under low coupling strength.

Proposal for a realtime Einstein-synchronization-defined satellite virtual clock

Realization of high performance satellite onboard clock is vital for various positioning, navigation, and timing applications. For further improvement of the synchronization-based satellite time and frequency references, we propose a geosynchronous(GEO) satellite virtual clock concept based on ground–satellite synchronization and present a beacon transponder structure for its implementation(scheduled for launch in 2025), which does not require atomic clocks to be mounted on the satellite. Its high performance relies only on minor modifications to the existing transponder structure of GEO satellites. We carefully model the carrier phase link and analyze the factors causing link asymmetry within the special relativity. Considering that performance of such synchronization-based satellite clocks is primarily limited by the link's random phase noise, which cannot be adequately modeled, we design a closed-loop experiment based on commercial GEO satellites for pre-evaluation. This experiment aims at extracting the zero-means random part of the ground-satellite Ku-band carrier phase via a feedback loop. Ultimately, we obtain a 1σ value of 0.633 ps(two-way link), following the Gaussian distribution. From this result, we conclude that the proposed real-time Einstein-synchronization-defined satellite virtual clock can achieve picosecond-level replication of onboard time and frequency.

Features of synchronous and metachronous dual primary gastric and colorectal cancer

BACKGROUND Studies evaluating the characteristics of dual primary gastric and colorectal cancer(CRC)(DPGCC)are limited.AIM To analyze the clinicopathologic characteristics and prognosis of synchronous and metachronous cancers in patients with DPGCC.METHODS From October 2010 to August 2021,patients with DPGCC were retrospectively reviewed.The patients with DPGCC were divided into two groups(synchronous and metachronous).We compared the overall survival(OS)between the groups using Kaplan-Meier survival methods.Univariate and multivariate analyses were performed using Cox’s proportional hazards model to identify the independent prognostic factors for OS.RESULTS Of the 76 patients with DPGCC,46 and 30 had synchronous and metachronous cancers,respectively.The proportion of unresectable CRC in patients with synchronous cancers was higher than that in patients with metachronous cancers(28.3%vs 3.3%,P=0.015).The majority of the second primary cancers had occurred within 5 years.Kaplan-Meier survival analysis showed that the patients with metachronous cancers had a better prognosis than patients with synchronous cancers(P=0.010).The patients who had undergone gastrectomy(P<0.001)or CRC resection(P<0.001)had a better prognosis than those who had not.In the multivariate analysis,synchronous cancer[hazard ratio(HR)=6.8,95%confidence interval(95%CI):2.0-22.7,(P=0.002)]and stage III-IV gastric cancer(GC)[HR=10.0,95%CI:3.4-29.5,(P<0.001)]were risk prognostic factor for OS,while patients who underwent gastrectomy was a protective prognostic factor for OS[HR=0.2,95%CI:0.1-0.6,P=0.002].CONCLUSION Regular surveillance for metachronous cancer is necessary during postoperative follow-up.Surgical resection is the mainstay of therapy to improve the prognosis of DPGCC.The prognosis appears to be influenced by the stage of GC rather than the stage of CRC.Patients with synchronous cancer have a worse prognosis,and its treatment strategy is worth further exploration.