Optical non-reciprocity is a fundamental phenomenon in photonics.It is crucial for developing devices that rely on directional signal control,such as optical isolators and circulators.However,most research in this fie...Optical non-reciprocity is a fundamental phenomenon in photonics.It is crucial for developing devices that rely on directional signal control,such as optical isolators and circulators.However,most research in this field has focused on systems in equilibrium or steady states.In this work,we demonstrate a room-temperature Rydberg atomic platform where the unidirectional propagation of light acts as a switch to mediate time-crystalline-like collective oscillations through atomic synchronization.展开更多
Clock synchronization has important applications in multi-agent collaboration(such as drone light shows,intelligent transportation systems,and game AI),group decision-making,and emergency rescue operations.Synchroniza...Clock synchronization has important applications in multi-agent collaboration(such as drone light shows,intelligent transportation systems,and game AI),group decision-making,and emergency rescue operations.Synchronization method based on pulse-coupled oscillators(PCOs)provides an effective solution for clock synchronization in wireless networks.However,the existing clock synchronization algorithms in multi-agent ad hoc networks are difficult to meet the requirements of high precision and high stability of synchronization clock in group cooperation.Hence,this paper constructs a network model,named DAUNet(unsupervised neural network based on dual attention),to enhance clock synchronization accuracy in multi-agent wireless ad hoc networks.Specifically,we design an unsupervised distributed neural network framework as the backbone,building upon classical PCO-based synchronization methods.This framework resolves issues such as prolonged time synchronization message exchange between nodes,difficulties in centralized node coordination,and challenges in distributed training.Furthermore,we introduce a dual-attention mechanism as the core module of DAUNet.By integrating a Multi-Head Attention module and a Gated Attention module,the model significantly improves information extraction capabilities while reducing computational complexity,effectively mitigating synchronization inaccuracies and instability in multi-agent ad hoc networks.To evaluate the effectiveness of the proposed model,comparative experiments and ablation studies were conducted against classical methods and existing deep learning models.The research results show that,compared with the deep learning networks based on DASA and LSTM,DAUNet can reduce the mean normalized phase difference(NPD)by 1 to 2 orders of magnitude.Compared with the attention models based on additive attention and self-attention mechanisms,the performance of DAUNet has improved by more than ten times.This study demonstrates DAUNet’s potential in advancing multi-agent ad hoc networking technologies.展开更多
With the increasing integration of renewable energy,microgrids are increasingly facing stability challenges,primarily due to the lack of inherent inertia in inverter-dominated systems,which is traditionally provided b...With the increasing integration of renewable energy,microgrids are increasingly facing stability challenges,primarily due to the lack of inherent inertia in inverter-dominated systems,which is traditionally provided by synchronous generators.To address this critical issue,Virtual Synchronous Generator(VSG)technology has emerged as a highly promising solution by emulating the inertia and damping characteristics of conventional synchronous generators.To enhance the operational efficiency of virtual synchronous generators(VSGs),this study employs smallsignal modeling analysis,root locus methods,and synchronous generator power-angle characteristic analysis to comprehensively evaluate how virtual inertia and damping coefficients affect frequency stability and power output during transient processes.Based on these analyses,an adaptive control strategy is proposed:increasing the virtual inertia when the rotor angular velocity undergoes rapid changes,while strengthening the damping coefficient when the speed deviation exceeds a certain threshold to suppress angular velocity oscillations.To validate the effectiveness of the proposed method,a grid-connected VSG simulation platform was developed inMATLAB/Simulink.Comparative simulations demonstrate that the proposed adaptive control strategy outperforms conventional VSGmethods by significantly reducing grid frequency deviations and shortening active power response time during active power command changes and load disturbances.This approach enhances microgrid stability and dynamic performance,confirming its viability for renewable-dominant power systems.Future work should focus on experimental validation and real-world parameter optimization,while further exploring the strategy’s effectiveness in improvingVSG low-voltage ride-through(LVRT)capability and power-sharing applications in multi-parallel configurations.展开更多
In this paper,the synchronizable system by groups and the generalized synchronizable system are studied for a coupled system of wave equations.Moreover,situations possessing different groupings are also discussed.
Projective synchronization and generalized projective synchronization have recently been observed in the coupled chaotic systems. In this paper, a new synchronization, called ＂generalized projective synchronization＂...Projective synchronization and generalized projective synchronization have recently been observed in the coupled chaotic systems. In this paper, a new synchronization, called ＂generalized projective synchronization＂, is reported in the chaotic Lorenz system and the chaotic Chen one.展开更多
This article briefly reviews the topic of complex network synchronization,with its graph-theoretic criterion,showing that the homogeneous and symmetrical network structures are essential for optimal synchronization.Fu...This article briefly reviews the topic of complex network synchronization,with its graph-theoretic criterion,showing that the homogeneous and symmetrical network structures are essential for optimal synchronization.Furthermore,it briefly reviews the notion of higher-order network topologies and shows their promising potential in application to evaluating the optimality of network synchronizability.展开更多
This paper propose a comprehensive data-driven prediction framework based on machine learning methods to investigate the lag synchronization phenomenon in coupled chaotic systems,particularly in cases where accurate m...This paper propose a comprehensive data-driven prediction framework based on machine learning methods to investigate the lag synchronization phenomenon in coupled chaotic systems,particularly in cases where accurate mathematical models are challenging to establish or where system equations remain unknown.The Long Short-Term Memory(LSTM)neural network is trained using time series acquired from the desynchronization system states,subsequently predicting the lag synchronization transition.In the experiments,we focus on the Lorenz system with time-varying delayed coupling,studying the effects of coupling coefficients and time delays on lag synchronization,respectively.The results indicate that with appropriate training,the machine learning model can adeptly predict the lag synchronization occurrence and transition.This study not only enhances our comprehension of complex network synchronization behaviors but also underscores the potential and practical applications of machine learning in exploring nonlinear dynamic systems.展开更多
Dear Editor,This letter deals with the controller synthesis problem of networked Takagi-Sugeno(T-S)fuzzy systems.Due to the introduction of network communications,the same premise is no longer shared by fuzzy plants a...Dear Editor,This letter deals with the controller synthesis problem of networked Takagi-Sugeno(T-S)fuzzy systems.Due to the introduction of network communications,the same premise is no longer shared by fuzzy plants and fuzzy controllers.This makes the classic parallel distribution compensation(PDC)control infeasible.To overcome this situation,a novel method for reconstructing the membership functions'grades is proposed,which synchronizes the time scales.Then,the membership function dependent method is adopted to introduce asynchronous errors and detailed membership function information.For the event-triggered control strategy,a series of robust H∞stable conditions in LMI form are derived.Finally,a simulation of a practical system is used to demonstrate the method proposed in this letter can reduce conservatism.展开更多
Dear Editor,This letter proposes a deep synchronization control(DSC) method to synchronize grid-forming converters with power grids. The method involves constructing a novel controller for grid-forming converters base...Dear Editor,This letter proposes a deep synchronization control(DSC) method to synchronize grid-forming converters with power grids. The method involves constructing a novel controller for grid-forming converters based on the stable deep dynamics model. To enhance the performance of the controller, the dynamics model is optimized within the deep reinforcement learning(DRL) framework. Simulation results verify that the proposed method can reduce frequency deviation and improve active power responses.展开更多
This study presents an emergency control method for sub-synchronous oscillations in wind power gridconnected systems based on transfer learning,addressing the issue of insufficient generalization ability of traditiona...This study presents an emergency control method for sub-synchronous oscillations in wind power gridconnected systems based on transfer learning,addressing the issue of insufficient generalization ability of traditional methods in complex real-world scenarios.By combining deep reinforcement learning with a transfer learning framework,cross-scenario knowledge transfer is achieved,significantly enhancing the adaptability of the control strategy.First,a sub-synchronous oscillation emergency control model for the wind power grid integration system is constructed under fixed scenarios based on deep reinforcement learning.A reward evaluation system based on the active power oscillation pattern of the system is proposed,introducing penalty functions for the number of machine-shedding rounds and the number of machines shed.This avoids the economic losses and grid security risks caused by the excessive one-time shedding of wind turbines.Furthermore,transfer learning is introduced into model training to enhance the model’s generalization capability in dealing with complex scenarios of actual wind power grid integration systems.By introducing the Maximum Mean Discrepancy(MMD)algorithm to calculate the distribution differences between source data and target data,the online decision-making reliability of the emergency control model is improved.Finally,the effectiveness of the proposed emergency control method for multi-scenario sub-synchronous oscillation in wind power grid integration systems based on transfer learning is analyzed using the New England 39-bus system.展开更多
This paper investigates robust unified （lag, anticipated, and complete） synchronization of two coupled chaotic systems, By introducing the concepts of positive definite symmetrical matrix and Riccati inequality and ...This paper investigates robust unified （lag, anticipated, and complete） synchronization of two coupled chaotic systems, By introducing the concepts of positive definite symmetrical matrix and Riccati inequality and the theory of robust stability, several criteria on robust synchronization are established. Extensive numerical simulations are also used to confirm the results.展开更多
This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-tri...This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.展开更多
The rise of time-sensitive applications with broad geographical scope drives the development of time-sensitive networking(TSN)from intra-domain to inter-domain to ensure overall end-to-end connectivity requirements in...The rise of time-sensitive applications with broad geographical scope drives the development of time-sensitive networking(TSN)from intra-domain to inter-domain to ensure overall end-to-end connectivity requirements in heterogeneous deployments.When multiple TSN networks interconnect over non-TSN networks,all devices in the network need to be syn-chronized by sharing a uniform time reference.How-ever,most non-TSN networks are best-effort.Path delay asymmetry and random noise accumulation can introduce unpredictable time errors during end-to-end time synchronization.These factors can degrade syn-chronization performance.Therefore,cross-domain time synchronization becomes a challenging issue for multiple TSN networks interconnected by non-TSN networks.This paper presents a cross-domain time synchronization scheme that follows the software-defined TSN(SD-TSN)paradigm.It utilizes a com-bined control plane constructed by a coordinate con-troller and a domain controller for centralized control and management of cross-domain time synchroniza-tion.The general operation flow of the cross-domain time synchronization process is designed.The mecha-nism of cross-domain time synchronization is revealed by introducing a synchronization model and an error compensation method.A TSN cross-domain proto-type testbed is constructed for verification.Results show that the scheme can achieve end-to-end high-precision time synchronization with accuracy and sta-bility.展开更多
Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and ev...Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.展开更多
Permanent magnet synchronous motor(PMSM),known for their compact size and high-power density,is widely used in fields such as electric vehicles and servo drives.However,traditional PID control methods for PMSM cannot ...Permanent magnet synchronous motor(PMSM),known for their compact size and high-power density,is widely used in fields such as electric vehicles and servo drives.However,traditional PID control methods for PMSM cannot dynamically adjust parameters according to varying operating conditions.To address this issue,this paper proposes a PID control method based on a radial basis function(RBF)neural network,which adaptively tunes the PID controller parameters.First,an offline RBF neural network with optimal structural parameters is trained using the current and speed data of the PMSM,and then employed to construct the RBF-PID controller.During online training,the Jacobian information calculated via the RBF neural network is used to adaptively adjust the PID parameters.Simultaneously,the structural parameters of the RBF network are updated in reverse based on the error between the predicted and reference speed values.Finally,numerical simulations and experiments in the context of electric vehicle drive control show that the maximum speed errors of the SMC controller and the RBF-PID controller are 1.97 km/h and 0.17 km/h,respectively.Moreover,the RBF-PID controller outperforms both the SMC and traditional PID controllers in handling sudden speed changes.展开更多
Recently,large-scale trapped ion systems have been realized in experiments for quantum simulation and quantum computation.They are the simplest systems for dynamical stability and parametric resonance.In this model,th...Recently,large-scale trapped ion systems have been realized in experiments for quantum simulation and quantum computation.They are the simplest systems for dynamical stability and parametric resonance.In this model,the Mathieu equation plays the most fundamental role for us to understand the stability and instability of a single ion.In this work,we investigate the dynamics of trapped ions with the Coulomb interaction based on the Hamiltonian equation.We show that the many-body interaction will not influence the phase diagram for instability.Then,the dynamics of this model in the large damping limit will also be analytically calculated using few trapped ions.Furthermore,we find that in the presence of modulation,synchronization dynamics can be observed,showing an exchange of velocities between distant ions on the left side and on the right side of the trap.These dynamics resemble that of the exchange of velocities in Newton's cradle for the collision of balls at the same time.These dynamics are independent of their initial conditions and the number of ions.As a unique feature of the interacting Mathieu equation,we hope this behavior,which leads to a quasi-periodic solution,can be measured in current experimental systems.Finally,we have also discussed the effect of anharmonic trapping potential,showing the desynchronization during the collision process.It is hoped that the dynamics in this many-body Mathieu equation with damping may find applications in quantum simulations.This model may also find interesting applications in dynamics systems as a pure mathematical problem,which may be beyond the results in the Floquet theorem.展开更多
This paper investigates modified fixed-time synchronization(FxTS)of complex networks(CNs)with time-varying delays based on continuous and discontinuous controllers.First,for the sake of making the settling time(ST)of ...This paper investigates modified fixed-time synchronization(FxTS)of complex networks(CNs)with time-varying delays based on continuous and discontinuous controllers.First,for the sake of making the settling time(ST)of FxTS is independent of the initial values and parameters of the CNs,a modified fixed-time(FxT)stability theorem is proposed,where the ST is determined by an arbitrary positive number given in advance.Then,continuous controller and discontinuous controller are designed to realize the modified FxTS target of CNs.In addition,based on the designed controllers,CNs can achieve synchronization at any given time,or even earlier.And control strategies effectively solve the problem of ST related to the parameters of CNs.Finally,an appropriate simulation example is conducted to examine the effectiveness of the designed control strategies.展开更多
Optical wireless(OW)communication systems face significant challenges such as signal attenuation due to atmospheric absorption,scattering,and noise from hardware components,which degrade detection sensitivity.To addre...Optical wireless(OW)communication systems face significant challenges such as signal attenuation due to atmospheric absorption,scattering,and noise from hardware components,which degrade detection sensitivity.To address these challenges,we propose a digital processing algorithm that combines finite impulse response filtering with dynamic synchronization based on pulse addition and subtraction.Unlike conventional methods,which typically rely solely on hardware optimization or basic thresholding techniques,the proposed approach integrates filtering and synchronization to improve weak signal detection and reduce noise-induced errors.The proposed algorithm was implemented and verified using a field-programmable gate array.Experiments conducted in an indoor OW communication environment demonstrate that the proposed algorithm significantly improves detection sensitivity by approximately 6 dB and 5 dB at communication rates of 3.5 Mbps and 5.0 Mbps,respectively.Specifically,under darkroom conditions and a bit error rate of 1×10^(-7),the detection sensitivity was improved from-38.56 dBm to-44.77 dBm at 3.5 Mbps and from-37.12 dBm to-42.29 dBm at 5 Mbps.The proposed algorithm is crucial for future capture and tracking of signals at large dispersion angles and in underwater and long-distance communication scenarios.展开更多
This paper explores the synchronization of stochastic simplicial complexes with noise,modeled by stochastic differential equations of It?type.It establishes the relationship between synchronization and individual dyna...This paper explores the synchronization of stochastic simplicial complexes with noise,modeled by stochastic differential equations of It?type.It establishes the relationship between synchronization and individual dynamics,higher-order structures,coupling strengths,and noise.In particular,this study delves into the role of multi-body interactions,particularly focusing on the influence of higher-order simplicial structures on the overall synchronization behavior.Furthermore,the effects of noise on synchronizability in the stochastic simplicial complex are thoroughly examined.The obtained results indicate that the effects of noise on the synchronizability vary with the manner in which noise propagates.The presence of noise can regulate the synchronization pattern of the simplicial complex,transforming the unstable state into a stable state,and vice versa.These findings offer valuable insights and a theoretical foundation for improving the performance of real-world networks,such as communication networks,biological systems,and social networks,where noise is often inevitable.展开更多
This study investigates chaotic synchronization via field-coupled nonlinear circuits, achieving both electrical synchronization and energy balance. The driving mechanism biomimetically parallels neuromuscular signal t...This study investigates chaotic synchronization via field-coupled nonlinear circuits, achieving both electrical synchronization and energy balance. The driving mechanism biomimetically parallels neuromuscular signal transduction, where synchronized neuronal firing induces coordinated muscle contractions that produce macroscopic movement. We implement a Chua circuit-driven robotic arm with tunable periodic/chaotic oscillations through parameter modulation and external current injection. Bifurcation analysis maps oscillation modes under varying external stimuli. Inductive coupling between two systems with distinct initial conditions facilitates magnetic energy transfer, optimized by an energy balance criterion. A bio-inspired exponential gain method dynamically regulates the coupling strength to optimize the energy transfer efficiency.The effects of ambient electromagnetic noise on synchronization are systematically quantified. The results indicate electrically modulatable robotic arm dynamics, with the coupled systems achieving autonomous rapid synchronization. Despite noise-induced desynchronization, inter-system errors rapidly decay and stabilize within bounded limits, confirming robust stability.展开更多
基金supported by the National Natural Science Foundation of China (Grant No.12274131)the Innovation Program for Quantum Science and Technology (Grant No.2024ZD0300101)。
文摘Optical non-reciprocity is a fundamental phenomenon in photonics.It is crucial for developing devices that rely on directional signal control,such as optical isolators and circulators.However,most research in this field has focused on systems in equilibrium or steady states.In this work,we demonstrate a room-temperature Rydberg atomic platform where the unidirectional propagation of light acts as a switch to mediate time-crystalline-like collective oscillations through atomic synchronization.
文摘Clock synchronization has important applications in multi-agent collaboration(such as drone light shows,intelligent transportation systems,and game AI),group decision-making,and emergency rescue operations.Synchronization method based on pulse-coupled oscillators(PCOs)provides an effective solution for clock synchronization in wireless networks.However,the existing clock synchronization algorithms in multi-agent ad hoc networks are difficult to meet the requirements of high precision and high stability of synchronization clock in group cooperation.Hence,this paper constructs a network model,named DAUNet(unsupervised neural network based on dual attention),to enhance clock synchronization accuracy in multi-agent wireless ad hoc networks.Specifically,we design an unsupervised distributed neural network framework as the backbone,building upon classical PCO-based synchronization methods.This framework resolves issues such as prolonged time synchronization message exchange between nodes,difficulties in centralized node coordination,and challenges in distributed training.Furthermore,we introduce a dual-attention mechanism as the core module of DAUNet.By integrating a Multi-Head Attention module and a Gated Attention module,the model significantly improves information extraction capabilities while reducing computational complexity,effectively mitigating synchronization inaccuracies and instability in multi-agent ad hoc networks.To evaluate the effectiveness of the proposed model,comparative experiments and ablation studies were conducted against classical methods and existing deep learning models.The research results show that,compared with the deep learning networks based on DASA and LSTM,DAUNet can reduce the mean normalized phase difference(NPD)by 1 to 2 orders of magnitude.Compared with the attention models based on additive attention and self-attention mechanisms,the performance of DAUNet has improved by more than ten times.This study demonstrates DAUNet’s potential in advancing multi-agent ad hoc networking technologies.
基金financially supported by the Talent Initiation Fund of Wuxi University(550220008).
文摘With the increasing integration of renewable energy,microgrids are increasingly facing stability challenges,primarily due to the lack of inherent inertia in inverter-dominated systems,which is traditionally provided by synchronous generators.To address this critical issue,Virtual Synchronous Generator(VSG)technology has emerged as a highly promising solution by emulating the inertia and damping characteristics of conventional synchronous generators.To enhance the operational efficiency of virtual synchronous generators(VSGs),this study employs smallsignal modeling analysis,root locus methods,and synchronous generator power-angle characteristic analysis to comprehensively evaluate how virtual inertia and damping coefficients affect frequency stability and power output during transient processes.Based on these analyses,an adaptive control strategy is proposed:increasing the virtual inertia when the rotor angular velocity undergoes rapid changes,while strengthening the damping coefficient when the speed deviation exceeds a certain threshold to suppress angular velocity oscillations.To validate the effectiveness of the proposed method,a grid-connected VSG simulation platform was developed inMATLAB/Simulink.Comparative simulations demonstrate that the proposed adaptive control strategy outperforms conventional VSGmethods by significantly reducing grid frequency deviations and shortening active power response time during active power command changes and load disturbances.This approach enhances microgrid stability and dynamic performance,confirming its viability for renewable-dominant power systems.Future work should focus on experimental validation and real-world parameter optimization,while further exploring the strategy’s effectiveness in improvingVSG low-voltage ride-through(LVRT)capability and power-sharing applications in multi-parallel configurations.
基金Supported by the National Natural Science Foundation of China(12301577)Sichuan Science and Technology Program(2023NSFSC1346).
文摘In this paper,the synchronizable system by groups and the generalized synchronizable system are studied for a coupled system of wave equations.Moreover,situations possessing different groupings are also discussed.
基金Project supported by Tianyuan Foundation of China （ Grant No. A0324651）, and Natural Science Foundation of Hunaa Province of China （Grant No. 03JJY3014）
文摘Projective synchronization and generalized projective synchronization have recently been observed in the coupled chaotic systems. In this paper, a new synchronization, called ＂generalized projective synchronization＂, is reported in the chaotic Lorenz system and the chaotic Chen one.
基金Hong Kong Research Grants Council under the GRF(9043664).
文摘This article briefly reviews the topic of complex network synchronization,with its graph-theoretic criterion,showing that the homogeneous and symmetrical network structures are essential for optimal synchronization.Furthermore,it briefly reviews the notion of higher-order network topologies and shows their promising potential in application to evaluating the optimality of network synchronizability.
基金supported by the National Natural Science Foundation of China(No.52174184)。
文摘This paper propose a comprehensive data-driven prediction framework based on machine learning methods to investigate the lag synchronization phenomenon in coupled chaotic systems,particularly in cases where accurate mathematical models are challenging to establish or where system equations remain unknown.The Long Short-Term Memory(LSTM)neural network is trained using time series acquired from the desynchronization system states,subsequently predicting the lag synchronization transition.In the experiments,we focus on the Lorenz system with time-varying delayed coupling,studying the effects of coupling coefficients and time delays on lag synchronization,respectively.The results indicate that with appropriate training,the machine learning model can adeptly predict the lag synchronization occurrence and transition.This study not only enhances our comprehension of complex network synchronization behaviors but also underscores the potential and practical applications of machine learning in exploring nonlinear dynamic systems.
基金supported by the National Natural Science Foundation of China(62173218,61833011)International International Cooperation Project of Shanghai Science and Technology Commission(21190780300).
文摘Dear Editor,This letter deals with the controller synthesis problem of networked Takagi-Sugeno(T-S)fuzzy systems.Due to the introduction of network communications,the same premise is no longer shared by fuzzy plants and fuzzy controllers.This makes the classic parallel distribution compensation(PDC)control infeasible.To overcome this situation,a novel method for reconstructing the membership functions'grades is proposed,which synchronizes the time scales.Then,the membership function dependent method is adopted to introduce asynchronous errors and detailed membership function information.For the event-triggered control strategy,a series of robust H∞stable conditions in LMI form are derived.Finally,a simulation of a practical system is used to demonstrate the method proposed in this letter can reduce conservatism.
基金supported in part by the National Natural Science Foundation of China(62033005,62273270)the Natural Science Foundation of Shaanxi Province(2023JC-XJ17)
文摘Dear Editor,This letter proposes a deep synchronization control(DSC) method to synchronize grid-forming converters with power grids. The method involves constructing a novel controller for grid-forming converters based on the stable deep dynamics model. To enhance the performance of the controller, the dynamics model is optimized within the deep reinforcement learning(DRL) framework. Simulation results verify that the proposed method can reduce frequency deviation and improve active power responses.
基金funded by Sponsorship of Science and Technology Project of State Grid Xinjiang Electric Power Co.,Ltd.,grant number SGXJ0000TKJS2400168.
文摘This study presents an emergency control method for sub-synchronous oscillations in wind power gridconnected systems based on transfer learning,addressing the issue of insufficient generalization ability of traditional methods in complex real-world scenarios.By combining deep reinforcement learning with a transfer learning framework,cross-scenario knowledge transfer is achieved,significantly enhancing the adaptability of the control strategy.First,a sub-synchronous oscillation emergency control model for the wind power grid integration system is constructed under fixed scenarios based on deep reinforcement learning.A reward evaluation system based on the active power oscillation pattern of the system is proposed,introducing penalty functions for the number of machine-shedding rounds and the number of machines shed.This avoids the economic losses and grid security risks caused by the excessive one-time shedding of wind turbines.Furthermore,transfer learning is introduced into model training to enhance the model’s generalization capability in dealing with complex scenarios of actual wind power grid integration systems.By introducing the Maximum Mean Discrepancy(MMD)algorithm to calculate the distribution differences between source data and target data,the online decision-making reliability of the emergency control model is improved.Finally,the effectiveness of the proposed emergency control method for multi-scenario sub-synchronous oscillation in wind power grid integration systems based on transfer learning is analyzed using the New England 39-bus system.
基金Project supported by the National Natural Science Foundation of China （Grant No 10372054）.
文摘This paper investigates robust unified （lag, anticipated, and complete） synchronization of two coupled chaotic systems, By introducing the concepts of positive definite symmetrical matrix and Riccati inequality and the theory of robust stability, several criteria on robust synchronization are established. Extensive numerical simulations are also used to confirm the results.
文摘This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.
基金supported in part by National Key R&D Program of China(Grant No.2022YFC3803700)in part by the National Natural Science Foundation of China(Grant No.92067102)in part by the project of Beijing Laboratory of Advanced Information Networks.
文摘The rise of time-sensitive applications with broad geographical scope drives the development of time-sensitive networking(TSN)from intra-domain to inter-domain to ensure overall end-to-end connectivity requirements in heterogeneous deployments.When multiple TSN networks interconnect over non-TSN networks,all devices in the network need to be syn-chronized by sharing a uniform time reference.How-ever,most non-TSN networks are best-effort.Path delay asymmetry and random noise accumulation can introduce unpredictable time errors during end-to-end time synchronization.These factors can degrade syn-chronization performance.Therefore,cross-domain time synchronization becomes a challenging issue for multiple TSN networks interconnected by non-TSN networks.This paper presents a cross-domain time synchronization scheme that follows the software-defined TSN(SD-TSN)paradigm.It utilizes a com-bined control plane constructed by a coordinate con-troller and a domain controller for centralized control and management of cross-domain time synchroniza-tion.The general operation flow of the cross-domain time synchronization process is designed.The mecha-nism of cross-domain time synchronization is revealed by introducing a synchronization model and an error compensation method.A TSN cross-domain proto-type testbed is constructed for verification.Results show that the scheme can achieve end-to-end high-precision time synchronization with accuracy and sta-bility.
基金Supported by the National Natural Science Foundation of China (11161027)。
文摘Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.
文摘Permanent magnet synchronous motor(PMSM),known for their compact size and high-power density,is widely used in fields such as electric vehicles and servo drives.However,traditional PID control methods for PMSM cannot dynamically adjust parameters according to varying operating conditions.To address this issue,this paper proposes a PID control method based on a radial basis function(RBF)neural network,which adaptively tunes the PID controller parameters.First,an offline RBF neural network with optimal structural parameters is trained using the current and speed data of the PMSM,and then employed to construct the RBF-PID controller.During online training,the Jacobian information calculated via the RBF neural network is used to adaptively adjust the PID parameters.Simultaneously,the structural parameters of the RBF network are updated in reverse based on the error between the predicted and reference speed values.Finally,numerical simulations and experiments in the context of electric vehicle drive control show that the maximum speed errors of the SMC controller and the RBF-PID controller are 1.97 km/h and 0.17 km/h,respectively.Moreover,the RBF-PID controller outperforms both the SMC and traditional PID controllers in handling sudden speed changes.
基金supported by the Innovation Program for Quantum Science and Technology(Grant Nos.2021ZD0301200,2021ZD0303200,and 2021ZD0301500)the Alliance of International Science Organizations(ANSO)。
文摘Recently,large-scale trapped ion systems have been realized in experiments for quantum simulation and quantum computation.They are the simplest systems for dynamical stability and parametric resonance.In this model,the Mathieu equation plays the most fundamental role for us to understand the stability and instability of a single ion.In this work,we investigate the dynamics of trapped ions with the Coulomb interaction based on the Hamiltonian equation.We show that the many-body interaction will not influence the phase diagram for instability.Then,the dynamics of this model in the large damping limit will also be analytically calculated using few trapped ions.Furthermore,we find that in the presence of modulation,synchronization dynamics can be observed,showing an exchange of velocities between distant ions on the left side and on the right side of the trap.These dynamics resemble that of the exchange of velocities in Newton's cradle for the collision of balls at the same time.These dynamics are independent of their initial conditions and the number of ions.As a unique feature of the interacting Mathieu equation,we hope this behavior,which leads to a quasi-periodic solution,can be measured in current experimental systems.Finally,we have also discussed the effect of anharmonic trapping potential,showing the desynchronization during the collision process.It is hoped that the dynamics in this many-body Mathieu equation with damping may find applications in quantum simulations.This model may also find interesting applications in dynamics systems as a pure mathematical problem,which may be beyond the results in the Floquet theorem.
基金Supported by the National Natural Science Foundation of China(62476082)。
文摘This paper investigates modified fixed-time synchronization(FxTS)of complex networks(CNs)with time-varying delays based on continuous and discontinuous controllers.First,for the sake of making the settling time(ST)of FxTS is independent of the initial values and parameters of the CNs,a modified fixed-time(FxT)stability theorem is proposed,where the ST is determined by an arbitrary positive number given in advance.Then,continuous controller and discontinuous controller are designed to realize the modified FxTS target of CNs.In addition,based on the designed controllers,CNs can achieve synchronization at any given time,or even earlier.And control strategies effectively solve the problem of ST related to the parameters of CNs.Finally,an appropriate simulation example is conducted to examine the effectiveness of the designed control strategies.
基金supported by National Key R&D Program of China under Grants No.2022YFB3902500,No.2022YFB2903402,and No.2021YFA0718804Natural Science Foundation of Jilin Province under Grant No.222621JC010297013Education Department of Jilin Province under Grant No.JJKH20220745KJ.
文摘Optical wireless(OW)communication systems face significant challenges such as signal attenuation due to atmospheric absorption,scattering,and noise from hardware components,which degrade detection sensitivity.To address these challenges,we propose a digital processing algorithm that combines finite impulse response filtering with dynamic synchronization based on pulse addition and subtraction.Unlike conventional methods,which typically rely solely on hardware optimization or basic thresholding techniques,the proposed approach integrates filtering and synchronization to improve weak signal detection and reduce noise-induced errors.The proposed algorithm was implemented and verified using a field-programmable gate array.Experiments conducted in an indoor OW communication environment demonstrate that the proposed algorithm significantly improves detection sensitivity by approximately 6 dB and 5 dB at communication rates of 3.5 Mbps and 5.0 Mbps,respectively.Specifically,under darkroom conditions and a bit error rate of 1×10^(-7),the detection sensitivity was improved from-38.56 dBm to-44.77 dBm at 3.5 Mbps and from-37.12 dBm to-42.29 dBm at 5 Mbps.The proposed algorithm is crucial for future capture and tracking of signals at large dispersion angles and in underwater and long-distance communication scenarios.
基金Project supported in part by the National Natural Science Foundation of China(Grant Nos.62473284,61973064,62203327)Hebei Natural Science Foundation(Grant No.F2022501024)。
文摘This paper explores the synchronization of stochastic simplicial complexes with noise,modeled by stochastic differential equations of It?type.It establishes the relationship between synchronization and individual dynamics,higher-order structures,coupling strengths,and noise.In particular,this study delves into the role of multi-body interactions,particularly focusing on the influence of higher-order simplicial structures on the overall synchronization behavior.Furthermore,the effects of noise on synchronizability in the stochastic simplicial complex are thoroughly examined.The obtained results indicate that the effects of noise on the synchronizability vary with the manner in which noise propagates.The presence of noise can regulate the synchronization pattern of the simplicial complex,transforming the unstable state into a stable state,and vice versa.These findings offer valuable insights and a theoretical foundation for improving the performance of real-world networks,such as communication networks,biological systems,and social networks,where noise is often inevitable.
基金Project supported by the National Key R&D Program of China (Grant No. 2023YFD2000601-02)。
文摘This study investigates chaotic synchronization via field-coupled nonlinear circuits, achieving both electrical synchronization and energy balance. The driving mechanism biomimetically parallels neuromuscular signal transduction, where synchronized neuronal firing induces coordinated muscle contractions that produce macroscopic movement. We implement a Chua circuit-driven robotic arm with tunable periodic/chaotic oscillations through parameter modulation and external current injection. Bifurcation analysis maps oscillation modes under varying external stimuli. Inductive coupling between two systems with distinct initial conditions facilitates magnetic energy transfer, optimized by an energy balance criterion. A bio-inspired exponential gain method dynamically regulates the coupling strength to optimize the energy transfer efficiency.The effects of ambient electromagnetic noise on synchronization are systematically quantified. The results indicate electrically modulatable robotic arm dynamics, with the coupled systems achieving autonomous rapid synchronization. Despite noise-induced desynchronization, inter-system errors rapidly decay and stabilize within bounded limits, confirming robust stability.
