This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramia...This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramians directly from the expansion coefficients of impulse responses.Leveraging these factors,we develop two model reduction algorithms that integrate the low-rank square root method with dominant subspace projection.Our method is computationally efficient and flexible,requiring only a few matrix-vector operations and a singular value decomposition of a low-dimensional matrix,thereby avoiding the need to solve differential Lyapunov equations.Numerical experiments confirm the effectiveness of the proposed approach.展开更多
The radio frequency(RF)fingerprint technique is a robust method for security enhancement of the physical layer by leveraging the unique RF imperfections inherent in various wireless devices.Among these imperfections,t...The radio frequency(RF)fingerprint technique is a robust method for security enhancement of the physical layer by leveraging the unique RF imperfections inherent in various wireless devices.Among these imperfections,the carrier frequency offset(CFO)stands out as a primary RF fingerprint(RFF)of the transmitter,offering the potential to distinguish among different transmitters.However,accurately estimating CFO in time-varying channels poses significant challenges due to multipath effects and Doppler shifts.In this paper,we focus on estimating CFO for wireless device identification in the orthogonal frequency division multiplexing(OFDM)communication system.To achieve precise CFO estimation under time-varying channels,we propose a frequency domain correlation and spline interpolation(FCSI)algorithm.This approach utilizes pilots distributed across different subcarriers to correlate with prior local sequences,facilitating accurate CFO estimation.Classification is then performed based on the Euclidean distance between the prior RFF and the tested RFF dataset.Simulation results demonstrate that the proposed Mconsecutive average method effectively reduces the classification error rate in the challenging high-frequency(HF)skywave channel environment.展开更多
Recently,the zeroing neural network(ZNN)has demonstrated remarkable effectiveness in tackling time-varying problems,delivering robust performance across both noise-free and noisy environments.However,existing ZNN mode...Recently,the zeroing neural network(ZNN)has demonstrated remarkable effectiveness in tackling time-varying problems,delivering robust performance across both noise-free and noisy environments.However,existing ZNN models are limited in their ability to actively suppress noise,which constrains their robustness and precision in solving time-varying problems.This paper introduces a novel active noise rejection ZNN(ANR-ZNN)design that enhances noise suppression by integrating computational error dynamics and harmonic behaviour.Through rigorous theoretical analysis,we demonstrate that the proposed ANR-ZNN maintains robust convergence in computational error performance under environmental noise.As a case study,the ANR-ZNN model is specifically applied to time-varying matrix inversion.Comprehensive computer simulations and robotic experiments further validate the ANR-ZNN's effectiveness,emphasising the proposed design's superiority and potential for solving time-varying problems.展开更多
This paper is dedicated to solving the problem of adaptive fuzzy fault-tolerant tracking control for a class of time-varying high-order uncertain nonlinear systems.The motivation comes from how to construct a compact ...This paper is dedicated to solving the problem of adaptive fuzzy fault-tolerant tracking control for a class of time-varying high-order uncertain nonlinear systems.The motivation comes from how to construct a compact set large enough in which the approximation of any unknown continuous function by a fuzzy logic system(FLS)is effective while compensating sensor/actuator faults and external disturbances.The difficulty is to verify the boundedness of closed-loop signals on the constructed compact set and to reduce the number of the variables of the fuzzy membership functions as many as possible.By a new lemma,linear/nonlinear terms are introduced in adaptive laws to dominate unknown residual terms.With adding a power integrator method,a unified fault-tolerant controller is designed to drive the tracking error to converge to a small compact set of the origin within a fixed time,regardless of whether the system suffers from faults and disturbances.Superior to the existing results,in the presence of time-varying factors the scheme of this paper clarifies the logical relationship between the compactness of the approximation and the boundedness of the state variables.Finally,the application of control strategy is demonstrated by numerical/practical examples.展开更多
This paper presents a copula technique to develop time-variant seismic fragility curves for corroded bridges at the system level and considers the realistic time-varying dependence among component seismic demands. Bas...This paper presents a copula technique to develop time-variant seismic fragility curves for corroded bridges at the system level and considers the realistic time-varying dependence among component seismic demands. Based on material deterioration mechanisms and incremental dynamic analysis, the time-evolving seismic demands of components were obtained in the form of marginal probability distributions. The time-varying dependences among bridge components were then captured with the best fitting copula function, which was selected from the commonly used copula classes by the empirical distribution based analysis method. The system time-variant fragility curves at different damage states were developed and the effects of time-varying dependences among components on the bridge system fragility were investigated. The results indicate the time-varying dependence among components significantly affects the time-variant fragility of the bridge system. The copula technique captures the nonlinear dependence among component seismic demands accurately and easily by separating the marginal distributions and the dependence among them.展开更多
A time-varying optimization strategy for battery cluster power allocation is proposed to minimize energy loss in battery energy storage systems(BESS).First,the time-dependent loss characteristics of both storage and n...A time-varying optimization strategy for battery cluster power allocation is proposed to minimize energy loss in battery energy storage systems(BESS).First,the time-dependent loss characteristics of both storage and non-storage components in BESS are ana-lyzed.Based on this analysis,steady-state and transient methods for evaluating battery loss are proposed.Second,considering the distinct time-varying characteristics of various BESS components,the load-rate vs.equivalent-efficiency curve and the current-loss power component gradient field are introduced as analytical tools.These tools facilitate the derivation of optimization path for both time-varying and time-invariant energy compo-nents of BESS.Building on this foundation,a time-varying optimization strategy for battery cluster power allocation is developed,aiming to minimize energy loss while fully accounting for the dynamic characteristics of BESS.Compared to real-time optimization,this strategy prioritizes global optimality in the time domain,mitigates the risk of dimensionality curse,and enhances BESS efficiency.Finally,a Simulink/Simscape model is established based on real-world data to simulate internal component losses within BESS.The effectiveness of the proposed strategy is validated under a peak shaving scenario.Results indicate that,after optimization,the annual operational loss of BESS is reduced by 2.40%,while the energy round-trip efficiency is improved by 0.59%.展开更多
This research considers the tracking problem of a moving target in distributed sensor networks with a limited sensing range(LSR)affected by non-Gaussian noise.In such sensor networks,observation loss due to LSR is a p...This research considers the tracking problem of a moving target in distributed sensor networks with a limited sensing range(LSR)affected by non-Gaussian noise.In such sensor networks,observation loss due to LSR is a prevalent issue that has received insufficient attention.We introduce a time-varying random variable to describe whether the sensor observes a moving target at each moment.When a single sensor node is unable to receive information from other nodes,it cannot update its state estimation of the moving target once the target moves beyond this node’s observation range.We propose an information flow topology within distributed sensor networks to facilitate the reception of prior state estimation data transmitted by neighboring nodes.Based on this information,a quadratic distributed estimator is designed for each sensor,and an output injection term is introduced to handle unstable systems.Finally,a numerical example is provided to illustrate the effectiveness of the proposed control scheme.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
Vaccination is critical for controlling infectious diseases,but negative vaccination information can lead to vaccine hesitancy.To study how the interplay between information diffusion and disease transmission impacts ...Vaccination is critical for controlling infectious diseases,but negative vaccination information can lead to vaccine hesitancy.To study how the interplay between information diffusion and disease transmission impacts vaccination and epidemic spread,we propose a novel two-layer multiplex network model that integrates an unaware-acceptant-negative-unaware(UANU)information diffusion model with a susceptible-vaccinated-exposed-infected-susceptible(SVEIS)epidemiological framework.This model includes individual exposure and vaccination statuses,time-varying forgetting probabilities,and information conversion thresholds.Through the microscopic Markov chain approach(MMCA),we derive dynamic transition equations and the epidemic threshold expression,validated by Monte Carlo simulations.Using MMCA equations,we predict vaccination densities and analyze parameter effects on vaccination,disease transmission,and the epidemic threshold.Our findings suggest that promoting positive information,curbing the spread of negative information,enhancing vaccine effectiveness,and promptly identifying asymptomatic carriers can significantly increase vaccination rates,reduce epidemic spread,and raise the epidemic threshold.展开更多
After a long period of water flooding development,the oilfield has entered the middle and high water cut stage.The physical properties of reservoirs are changed by water erosion,which directly impacts reservoir develo...After a long period of water flooding development,the oilfield has entered the middle and high water cut stage.The physical properties of reservoirs are changed by water erosion,which directly impacts reservoir development.Conventional numerical reservoir simulation methodologies typically employ static assumptions for model construction,presuming invariant reservoir geological parameters throughout the development process while neglecting the reservoir’s temporal evolution characteristics.Although such simplifications reduce computational complexity,they introduce substantial descriptive inaccuracies.Therefore,this paper proposes a meshless numerical simulation method for reservoirs that considers time-varying characteristics.This method avoids the meshing in traditional numerical simulation methods.From the fluid flow perspective,the reservoir’s computational domain is discretized into a series of connection units.An influence domain with a certain radius centered on the nodes is selected,and one-dimensional connection units are established between the nodes to achieve the characterization of the flow topology structure of the reservoir.In order to reflect the dynamic evolution of the reservoir’s physical properties during the water injection development process,the time-varying characteristics are incorporated into the formula of the seepage characteristic parameters in the meshless calculation.The change relationship of the permeability under different surface fluxes is considered to update the calculated connection conductivity in real time.By combining with the seepage control equation for solution,a time-varying meshless numerical simulation method is formed.The results show that compared with the numerical simulationmethod of the connection elementmethod(CEM)that only considers static parameters,this method has higher simulation accuracy and can better simulate the real migration and distribution of oil and water in the reservoir.Thismethod improves the accuracy of reservoir numerical simulation and the development effect of oilfields,providing a scientific basis for optimizing the water injection strategy,adjusting the production plan,and extending the effective production cycle of the oilfield.展开更多
This paper study the finite time internal synchronization and the external synchronization(hybrid synchronization)for duplex heterogeneous complex networks by time-varying intermittent control.There few study hybrid s...This paper study the finite time internal synchronization and the external synchronization(hybrid synchronization)for duplex heterogeneous complex networks by time-varying intermittent control.There few study hybrid synchronization of heterogeneous duplex complex networks.Therefore,we study the finite time hybrid synchronization of heterogeneous duplex networks,which employs the time-varying intermittent control to drive the duplex heterogeneous complex networks to achieve hybrid synchronization in finite time.To be specific,the switch frequency of the controllers can be changed with time by devise Lyapunov function and boundary function,the internal synchronization and external synchronization are achieved simultaneously in finite time.Finally,numerical examples are presented to illustrate the validness of theoretical results.展开更多
This paper considers adaptive event-triggered stabilization for a class of uncertain time-varying nonlinear systems.Remarkably,the systems contain intrinsic time-varying unknown parameters which are allowed to be non-...This paper considers adaptive event-triggered stabilization for a class of uncertain time-varying nonlinear systems.Remarkably,the systems contain intrinsic time-varying unknown parameters which are allowed to be non-differentiable and in turn can be fast-varying.Moreover,the systems admit unknown control directions.To counteract the different uncertainties,more than one compensation mechanism has to be incorporated.However,in the context of event-triggered control,ensuring the effectiveness of these compensation mechanisms under reduced execution necessitates delicate design and analysis.This paper proposes a tight and powerful strategy for adaptive event-triggered control(ETC)by integrating the state-of-the-art adaptive techniques.In particular,the strategy substantially mitigates the conservatism caused by repetitive inequality-based treatments of uncertainties.Specifically,by leveraging the congelation-of-variables method and tuning functions,the conservatism in the treatment of the fast-varying parameters is significantly reduced.With multiple Nussbaum functions employed to handle unknown control directions,a set of dynamic compensations is designed to counteract unknown amplitudes of control coefficients without relying on inequality-based treatments.Moreover,a dedicated dynamic compensation is introduced to deal with the control coefficient coupled with the execution error,based on which a relativethreshold event-triggering mechanism(ETM)is rigorously validated.It turns out that the adaptive event-triggered controller achieves the closed-loop convergence while guaranteeing a uniform lower bound for inter-execution times.Simulation results verify the effectiveness and superiority of the proposed strategy.展开更多
This paper investigates the observer-based prescribed-time time-varying output formation-containment(PT-TV-OFC)control problem for heterogeneous multi-agent systems in which the different agents have different state d...This paper investigates the observer-based prescribed-time time-varying output formation-containment(PT-TV-OFC)control problem for heterogeneous multi-agent systems in which the different agents have different state dimensions.The system comprises one tracking leader,multiple formation leaders,and followers,where two types of leaders are used to generate a reference trajectory for movement and achieve specific formation,respectively.Firstly,a prescribed-time dynamics observer is constructed for the formation leaders to estimate the tracking leader's dynamic model and state.On this basis,a prescribed-time control protocol is designed for the formation leaders to achieve time-varying output formation.Then,a prescribed-time convex hull observer is designed for the followers to estimate information regarding the convex hull formed by the formation leaders.Using the estimated convex hull information,a prescribed-time containment control protocol is designed to ensure the followers converge into the convex hull.Furthermore,using Lyapunov stability theory,the stability of systems is proved in detail,which implies that the heterogeneous multi-agent systems can achieve PT-TV-OFC control.Finally,numerical simulations validate the feasibility of the theoretical results.展开更多
The time-varying periodic variations in Global Navigation Satellite System(GNSS)stations affect the reliable time series analysis and appropriate geophysical interpretation.In this study,we apply the singular spectrum...The time-varying periodic variations in Global Navigation Satellite System(GNSS)stations affect the reliable time series analysis and appropriate geophysical interpretation.In this study,we apply the singular spectrum analysis(SSA)method to characterize and interpret the periodic patterns of GNSS deformations in China using multiple geodetic datasets.These include 23-year observations from the Crustal Movement Observation Network of China(CMONOC),displacements inferred from the Gravity Recovery and Climate Experiment(GRACE),and loadings derived from Geophysical models(GM).The results reveal that all CMONOC time series exhibit seasonal signals characterized by amplitude and phase modulations,and the SSA method outperforms the traditional least squares fitting(LSF)method in extracting and interpreting the time-varying seasonal signals from the original time series.The decrease in the root mean square(RMS)correlates well with the annual cycle variance estimated by the SSA method,and the average reduction in noise amplitudes is nearly twice as much for SSA filtered results compared with those from the LSF method.With SSA analysis,the time-varying seasonal signals for all the selected stations can be identified in the reconstructed components corresponding to the first ten eigenvalues.Moreover,both RMS reduction and correlation analysis imply the advantages of GRACE solutions in explaining the GNSS periodic variations,and the geophysical effects can account for 71%of the GNSS annual amplitudes,and the average RMS reduction is 15%.The SSA method has proved to be useful for investigating the GNSS timevarying seasonal signals.It could be applicable as an auxiliary tool in the improvement of nonlinear variations investigations.展开更多
With the growing adoption of artificial intelligence algorithms and neural networks,online learning and adaptive methods for updating the bandwidth have become increasingly prevalent.However,the conditions required to...With the growing adoption of artificial intelligence algorithms and neural networks,online learning and adaptive methods for updating the bandwidth have become increasingly prevalent.However,the conditions required to ensure closed-loop stability when employing a time-varying bandwidth,as well as the supporting mathematical foundations,remain insufficiently studied.This paper investigates the stability condition for active disturbance rejection control(ADRC)with a time-varying bandwidth extended state observer(ESO).A new stability condition is derived,which means that the upper bound of rate of change for ESO bandwidth should be restricted.Moreover,under the proposed condition,the closed-loop stability of ADRC with a time-varying bandwidth observer is rigorously proved for nonlinear uncertainties.In simulations,the necessity of the proposed condition is illustrated,demonstrating that the rate of change of ESO bandwidth is crucial for closed-loop stability.展开更多
This study examines the dynamic interplay between the US Dollar Index(USDI)and gold prices(GP)to assess the sustainability of gold price trends.Employing a rolling window bootstrapping causality test methodology acros...This study examines the dynamic interplay between the US Dollar Index(USDI)and gold prices(GP)to assess the sustainability of gold price trends.Employing a rolling window bootstrapping causality test methodology across full and sub-samples,the findings of this study challenge the conventional assumption of a stable long-term inverse correlation between USDI and GP,thereby validating the hypothesis that their relationship is nonlinear and time-dependent.During periods of heightened geopolitical and economic volatility,both the US dollar and gold function as safe-haven assets,with USDI fluctuations exerting a positive influence on GP.Conversely,under stable market conditions,the US dollar serves as the currency in which gold is denominated,resulting in a negative impact of USDI on GP.Notably,GP also demonstrates bidirectional causality,exhibiting both positive and negative effects on USDI.The analysis reveals that while a general inverse correlation persists between gold and the US dollar,this relationship transitions to positive during surges in global political and economic instability.In light of contemporary developments—including escalating geopolitical rivalries,tepid post-pandemic economic recovery,and elevated US interest rates driven by inflationary pressures—this study posit that the upward trajectory of gold prices retains a robust empirical foundation.展开更多
This paper establishes a method for identifying and locating dynamic loads in time-varying systems.The proposed method linearizes time-varying parameters within small time units and uses the Wilson-θ inverse analysis...This paper establishes a method for identifying and locating dynamic loads in time-varying systems.The proposed method linearizes time-varying parameters within small time units and uses the Wilson-θ inverse analysis method to solve modal loads of each order at each time step.It then uses an exhaustive method to determine the load position.Finally,it calculates the time history of the load.Simulation examples demonstrate how the number of measuring points and step size affect load identi-fication accuracy,verifying that this algorithm achieves good identification accuracy for loads under resonance conditions.Additionally,it explores how noise affects load position and recognition accuracy,while providing a solution.Simulation examples and experimental results demonstrate that the proposed method can identify both the time history and position of loads simultaneously with high identification accuracy.展开更多
This paper investigates a class of constrained distributed zeroth-order optimization(ZOO) problems over timevarying unbalanced graphs while ensuring privacy preservation among individual agents. Not taking into accoun...This paper investigates a class of constrained distributed zeroth-order optimization(ZOO) problems over timevarying unbalanced graphs while ensuring privacy preservation among individual agents. Not taking into account recent progress and addressing these concerns separately, there remains a lack of solutions offering theoretical guarantees for both privacy protection and constrained ZOO over time-varying unbalanced graphs.We hereby propose a novel algorithm, termed the differential privacy(DP) distributed push-sum based zeroth-order constrained optimization algorithm(DP-ZOCOA). Operating over time-varying unbalanced graphs, DP-ZOCOA obviates the need for supplemental suboptimization problem computations, thereby reducing overhead in comparison to distributed primary-dual methods. DP-ZOCOA is specifically tailored to tackle constrained ZOO problems over time-varying unbalanced graphs,offering a guarantee of convergence to the optimal solution while robustly preserving privacy. Moreover, we provide rigorous proofs of convergence and privacy for DP-ZOCOA, underscoring its efficacy in attaining optimal convergence without constraints. To enhance its applicability, we incorporate DP-ZOCOA into the federated learning framework and formulate a decentralized zeroth-order constrained federated learning algorithm(ZOCOA-FL) to address challenges stemming from the timevarying imbalance of communication topology. Finally, the performance and effectiveness of the proposed algorithms are thoroughly evaluated through simulations on distributed least squares(DLS) and decentralized federated learning(DFL) tasks.展开更多
The dynamics of network power response play a crucial role in system stability.However,the integration of power electronic equipment leads to amplitude and angular frequency(abbreviated as"frequency")time-va...The dynamics of network power response play a crucial role in system stability.However,the integration of power electronic equipment leads to amplitude and angular frequency(abbreviated as"frequency")time-varying characteristics of the node voltage during dynamic processes.As a result,traditional calcu-lation methods for and characteristics of the power response of the network based on phasor and impe-dance lose their validity.Therefore,this paper undertakes mathematical calculations to reveal the power response of a network under excitation by voltage with time-varying amplitude and frequency(TVAF),relying on the original mathematical relationships and superimposed step response.Then,the multi-timescale characteristics of both the active and reactive power of the network are explored physically.Additionally,this paper reveals a new phenomenon of storing and releasing the active and reactive power of the network.To meet practical engineering requirements,a simplified power expression is presented.Finally,the theoretical analysis is validated through time-domain simulations.展开更多
An eigenaxis maneuver strategy with global robustness is studied for large angle attitude maneuver of rigid spacecraft. A sliding mode attitude control algorithm with an exponential time-varying sliding surface is des...An eigenaxis maneuver strategy with global robustness is studied for large angle attitude maneuver of rigid spacecraft. A sliding mode attitude control algorithm with an exponential time-varying sliding surface is designed, which guarantees the sliding mode occurrence at the beginning and eliminates the reaching phase of time-invariant sliding mode control. The proposed control law is global robust against matched external disturbances and system uncertainties, and ensures the eigenaxis rotation in the presence of disturbances and parametric uncertainties. The stability of the control law and the existence of global siding mode are proved by Lyapunov method. Furthermore, the system states can be fully predicted by the analytical solution of state equations, which indicates that the attitude error does not exhibit any overshoots and the system has a good dynamic response. A control torque command regulator is introduced to ensure the eigenaxis rotation under the actuator saturation. Finally, a numerical simulation is employed to illustrate the advantages of the proposed control law.展开更多
文摘This paper presents an efficient model reduction technique for linear time-varying systems based on shifted Legendre polynomials.The approach constructs approximate low-rank decomposition factors of finite-time Gramians directly from the expansion coefficients of impulse responses.Leveraging these factors,we develop two model reduction algorithms that integrate the low-rank square root method with dominant subspace projection.Our method is computationally efficient and flexible,requiring only a few matrix-vector operations and a singular value decomposition of a low-dimensional matrix,thereby avoiding the need to solve differential Lyapunov equations.Numerical experiments confirm the effectiveness of the proposed approach.
基金supported by ZTE Industry-University-Institute Cooperation Funds under Grant No.IA20240723011National Natural Science Foundation of China under Grant No.62371123+1 种基金Young Elite Scientists Sponsorship Program of the Beijing High Innovation Plan under Grant No.20251077Research Fund of National Mobile Communications Research Laboratory,Southeast University under Grant No.2023A03。
文摘The radio frequency(RF)fingerprint technique is a robust method for security enhancement of the physical layer by leveraging the unique RF imperfections inherent in various wireless devices.Among these imperfections,the carrier frequency offset(CFO)stands out as a primary RF fingerprint(RFF)of the transmitter,offering the potential to distinguish among different transmitters.However,accurately estimating CFO in time-varying channels poses significant challenges due to multipath effects and Doppler shifts.In this paper,we focus on estimating CFO for wireless device identification in the orthogonal frequency division multiplexing(OFDM)communication system.To achieve precise CFO estimation under time-varying channels,we propose a frequency domain correlation and spline interpolation(FCSI)algorithm.This approach utilizes pilots distributed across different subcarriers to correlate with prior local sequences,facilitating accurate CFO estimation.Classification is then performed based on the Euclidean distance between the prior RFF and the tested RFF dataset.Simulation results demonstrate that the proposed Mconsecutive average method effectively reduces the classification error rate in the challenging high-frequency(HF)skywave channel environment.
基金supported by the National Science and Technology Major Project(2022ZD0119901)the National Natural Science Foundation of China under Grant(U2141234,62463004 and U24A20260)+1 种基金the Hainan Province Science and Technology Special Fund(ZDYF2024GXJS003)the Scientific Research Fund of Hainan University(KYQD(ZR)23025).
文摘Recently,the zeroing neural network(ZNN)has demonstrated remarkable effectiveness in tackling time-varying problems,delivering robust performance across both noise-free and noisy environments.However,existing ZNN models are limited in their ability to actively suppress noise,which constrains their robustness and precision in solving time-varying problems.This paper introduces a novel active noise rejection ZNN(ANR-ZNN)design that enhances noise suppression by integrating computational error dynamics and harmonic behaviour.Through rigorous theoretical analysis,we demonstrate that the proposed ANR-ZNN maintains robust convergence in computational error performance under environmental noise.As a case study,the ANR-ZNN model is specifically applied to time-varying matrix inversion.Comprehensive computer simulations and robotic experiments further validate the ANR-ZNN's effectiveness,emphasising the proposed design's superiority and potential for solving time-varying problems.
基金supported by National Natural Science Foundation of China[grant number 62173208]Taishan Scholar Project of Shandong Province of China[grant number tsqn202103061]。
文摘This paper is dedicated to solving the problem of adaptive fuzzy fault-tolerant tracking control for a class of time-varying high-order uncertain nonlinear systems.The motivation comes from how to construct a compact set large enough in which the approximation of any unknown continuous function by a fuzzy logic system(FLS)is effective while compensating sensor/actuator faults and external disturbances.The difficulty is to verify the boundedness of closed-loop signals on the constructed compact set and to reduce the number of the variables of the fuzzy membership functions as many as possible.By a new lemma,linear/nonlinear terms are introduced in adaptive laws to dominate unknown residual terms.With adding a power integrator method,a unified fault-tolerant controller is designed to drive the tracking error to converge to a small compact set of the origin within a fixed time,regardless of whether the system suffers from faults and disturbances.Superior to the existing results,in the presence of time-varying factors the scheme of this paper clarifies the logical relationship between the compactness of the approximation and the boundedness of the state variables.Finally,the application of control strategy is demonstrated by numerical/practical examples.
基金Natural Science Foundation of China under Grant No.51808376
文摘This paper presents a copula technique to develop time-variant seismic fragility curves for corroded bridges at the system level and considers the realistic time-varying dependence among component seismic demands. Based on material deterioration mechanisms and incremental dynamic analysis, the time-evolving seismic demands of components were obtained in the form of marginal probability distributions. The time-varying dependences among bridge components were then captured with the best fitting copula function, which was selected from the commonly used copula classes by the empirical distribution based analysis method. The system time-variant fragility curves at different damage states were developed and the effects of time-varying dependences among components on the bridge system fragility were investigated. The results indicate the time-varying dependence among components significantly affects the time-variant fragility of the bridge system. The copula technique captures the nonlinear dependence among component seismic demands accurately and easily by separating the marginal distributions and the dependence among them.
基金supported by Key Program of the Na-tional Natural Science Foundation of China(No.52337004).
文摘A time-varying optimization strategy for battery cluster power allocation is proposed to minimize energy loss in battery energy storage systems(BESS).First,the time-dependent loss characteristics of both storage and non-storage components in BESS are ana-lyzed.Based on this analysis,steady-state and transient methods for evaluating battery loss are proposed.Second,considering the distinct time-varying characteristics of various BESS components,the load-rate vs.equivalent-efficiency curve and the current-loss power component gradient field are introduced as analytical tools.These tools facilitate the derivation of optimization path for both time-varying and time-invariant energy compo-nents of BESS.Building on this foundation,a time-varying optimization strategy for battery cluster power allocation is developed,aiming to minimize energy loss while fully accounting for the dynamic characteristics of BESS.Compared to real-time optimization,this strategy prioritizes global optimality in the time domain,mitigates the risk of dimensionality curse,and enhances BESS efficiency.Finally,a Simulink/Simscape model is established based on real-world data to simulate internal component losses within BESS.The effectiveness of the proposed strategy is validated under a peak shaving scenario.Results indicate that,after optimization,the annual operational loss of BESS is reduced by 2.40%,while the energy round-trip efficiency is improved by 0.59%.
基金National Natural Science Foundation of China(No.61803081)。
文摘This research considers the tracking problem of a moving target in distributed sensor networks with a limited sensing range(LSR)affected by non-Gaussian noise.In such sensor networks,observation loss due to LSR is a prevalent issue that has received insufficient attention.We introduce a time-varying random variable to describe whether the sensor observes a moving target at each moment.When a single sensor node is unable to receive information from other nodes,it cannot update its state estimation of the moving target once the target moves beyond this node’s observation range.We propose an information flow topology within distributed sensor networks to facilitate the reception of prior state estimation data transmitted by neighboring nodes.Based on this information,a quadratic distributed estimator is designed for each sensor,and an output injection term is introduced to handle unstable systems.Finally,a numerical example is provided to illustrate the effectiveness of the proposed control scheme.
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 the National Social Science Foundation of China(Grant Nos.21BGL217 and 22CGL050)the Philosophy and Social Science Fund of Education Department of Jiangsu Province(Grant No.2020SJA2346).
文摘Vaccination is critical for controlling infectious diseases,but negative vaccination information can lead to vaccine hesitancy.To study how the interplay between information diffusion and disease transmission impacts vaccination and epidemic spread,we propose a novel two-layer multiplex network model that integrates an unaware-acceptant-negative-unaware(UANU)information diffusion model with a susceptible-vaccinated-exposed-infected-susceptible(SVEIS)epidemiological framework.This model includes individual exposure and vaccination statuses,time-varying forgetting probabilities,and information conversion thresholds.Through the microscopic Markov chain approach(MMCA),we derive dynamic transition equations and the epidemic threshold expression,validated by Monte Carlo simulations.Using MMCA equations,we predict vaccination densities and analyze parameter effects on vaccination,disease transmission,and the epidemic threshold.Our findings suggest that promoting positive information,curbing the spread of negative information,enhancing vaccine effectiveness,and promptly identifying asymptomatic carriers can significantly increase vaccination rates,reduce epidemic spread,and raise the epidemic threshold.
基金funded by the 14th Five-Year Plan Major Science and Technology Project of CNOOC project number KJGG2021-0506.
文摘After a long period of water flooding development,the oilfield has entered the middle and high water cut stage.The physical properties of reservoirs are changed by water erosion,which directly impacts reservoir development.Conventional numerical reservoir simulation methodologies typically employ static assumptions for model construction,presuming invariant reservoir geological parameters throughout the development process while neglecting the reservoir’s temporal evolution characteristics.Although such simplifications reduce computational complexity,they introduce substantial descriptive inaccuracies.Therefore,this paper proposes a meshless numerical simulation method for reservoirs that considers time-varying characteristics.This method avoids the meshing in traditional numerical simulation methods.From the fluid flow perspective,the reservoir’s computational domain is discretized into a series of connection units.An influence domain with a certain radius centered on the nodes is selected,and one-dimensional connection units are established between the nodes to achieve the characterization of the flow topology structure of the reservoir.In order to reflect the dynamic evolution of the reservoir’s physical properties during the water injection development process,the time-varying characteristics are incorporated into the formula of the seepage characteristic parameters in the meshless calculation.The change relationship of the permeability under different surface fluxes is considered to update the calculated connection conductivity in real time.By combining with the seepage control equation for solution,a time-varying meshless numerical simulation method is formed.The results show that compared with the numerical simulationmethod of the connection elementmethod(CEM)that only considers static parameters,this method has higher simulation accuracy and can better simulate the real migration and distribution of oil and water in the reservoir.Thismethod improves the accuracy of reservoir numerical simulation and the development effect of oilfields,providing a scientific basis for optimizing the water injection strategy,adjusting the production plan,and extending the effective production cycle of the oilfield.
基金Project supported by Jilin Provincial Science and Technology Development Plan(Grant No.20220101137JC).
文摘This paper study the finite time internal synchronization and the external synchronization(hybrid synchronization)for duplex heterogeneous complex networks by time-varying intermittent control.There few study hybrid synchronization of heterogeneous duplex complex networks.Therefore,we study the finite time hybrid synchronization of heterogeneous duplex networks,which employs the time-varying intermittent control to drive the duplex heterogeneous complex networks to achieve hybrid synchronization in finite time.To be specific,the switch frequency of the controllers can be changed with time by devise Lyapunov function and boundary function,the internal synchronization and external synchronization are achieved simultaneously in finite time.Finally,numerical examples are presented to illustrate the validness of theoretical results.
基金supported in part by the National Natural Science Foundation of China(62033007)the Fundamental Research Program of Shandong Province(ZR2023ZD37).
文摘This paper considers adaptive event-triggered stabilization for a class of uncertain time-varying nonlinear systems.Remarkably,the systems contain intrinsic time-varying unknown parameters which are allowed to be non-differentiable and in turn can be fast-varying.Moreover,the systems admit unknown control directions.To counteract the different uncertainties,more than one compensation mechanism has to be incorporated.However,in the context of event-triggered control,ensuring the effectiveness of these compensation mechanisms under reduced execution necessitates delicate design and analysis.This paper proposes a tight and powerful strategy for adaptive event-triggered control(ETC)by integrating the state-of-the-art adaptive techniques.In particular,the strategy substantially mitigates the conservatism caused by repetitive inequality-based treatments of uncertainties.Specifically,by leveraging the congelation-of-variables method and tuning functions,the conservatism in the treatment of the fast-varying parameters is significantly reduced.With multiple Nussbaum functions employed to handle unknown control directions,a set of dynamic compensations is designed to counteract unknown amplitudes of control coefficients without relying on inequality-based treatments.Moreover,a dedicated dynamic compensation is introduced to deal with the control coefficient coupled with the execution error,based on which a relativethreshold event-triggering mechanism(ETM)is rigorously validated.It turns out that the adaptive event-triggered controller achieves the closed-loop convergence while guaranteeing a uniform lower bound for inter-execution times.Simulation results verify the effectiveness and superiority of the proposed strategy.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.62473135 and 62173121)。
文摘This paper investigates the observer-based prescribed-time time-varying output formation-containment(PT-TV-OFC)control problem for heterogeneous multi-agent systems in which the different agents have different state dimensions.The system comprises one tracking leader,multiple formation leaders,and followers,where two types of leaders are used to generate a reference trajectory for movement and achieve specific formation,respectively.Firstly,a prescribed-time dynamics observer is constructed for the formation leaders to estimate the tracking leader's dynamic model and state.On this basis,a prescribed-time control protocol is designed for the formation leaders to achieve time-varying output formation.Then,a prescribed-time convex hull observer is designed for the followers to estimate information regarding the convex hull formed by the formation leaders.Using the estimated convex hull information,a prescribed-time containment control protocol is designed to ensure the followers converge into the convex hull.Furthermore,using Lyapunov stability theory,the stability of systems is proved in detail,which implies that the heterogeneous multi-agent systems can achieve PT-TV-OFC control.Finally,numerical simulations validate the feasibility of the theoretical results.
基金supported by the National Natural Science Foundation of China(NO.42104028,42174030 and 42004017)the Open Fund of Hubei Luojia Laboratory(No.220100048 and 230100021)the Scientific Research Project of Hubei Provincial Department of Education,and Research Foundation of the Department of Natural Resources of Hunan Province(No.20230104CH)。
文摘The time-varying periodic variations in Global Navigation Satellite System(GNSS)stations affect the reliable time series analysis and appropriate geophysical interpretation.In this study,we apply the singular spectrum analysis(SSA)method to characterize and interpret the periodic patterns of GNSS deformations in China using multiple geodetic datasets.These include 23-year observations from the Crustal Movement Observation Network of China(CMONOC),displacements inferred from the Gravity Recovery and Climate Experiment(GRACE),and loadings derived from Geophysical models(GM).The results reveal that all CMONOC time series exhibit seasonal signals characterized by amplitude and phase modulations,and the SSA method outperforms the traditional least squares fitting(LSF)method in extracting and interpreting the time-varying seasonal signals from the original time series.The decrease in the root mean square(RMS)correlates well with the annual cycle variance estimated by the SSA method,and the average reduction in noise amplitudes is nearly twice as much for SSA filtered results compared with those from the LSF method.With SSA analysis,the time-varying seasonal signals for all the selected stations can be identified in the reconstructed components corresponding to the first ten eigenvalues.Moreover,both RMS reduction and correlation analysis imply the advantages of GRACE solutions in explaining the GNSS periodic variations,and the geophysical effects can account for 71%of the GNSS annual amplitudes,and the average RMS reduction is 15%.The SSA method has proved to be useful for investigating the GNSS timevarying seasonal signals.It could be applicable as an auxiliary tool in the improvement of nonlinear variations investigations.
基金supported partially by the National Natural Science Foundation(No.62473344)the T-Flight Laboratory in ShanXi Provincial(No.GSFC2024NBKY05)+1 种基金the Natural Science Basic Research Program of Shaanxi(No.2025JC-YBQN-035)the National Natural Science Foundation of China(Grant No.92471204).
文摘With the growing adoption of artificial intelligence algorithms and neural networks,online learning and adaptive methods for updating the bandwidth have become increasingly prevalent.However,the conditions required to ensure closed-loop stability when employing a time-varying bandwidth,as well as the supporting mathematical foundations,remain insufficiently studied.This paper investigates the stability condition for active disturbance rejection control(ADRC)with a time-varying bandwidth extended state observer(ESO).A new stability condition is derived,which means that the upper bound of rate of change for ESO bandwidth should be restricted.Moreover,under the proposed condition,the closed-loop stability of ADRC with a time-varying bandwidth observer is rigorously proved for nonlinear uncertainties.In simulations,the necessity of the proposed condition is illustrated,demonstrating that the rate of change of ESO bandwidth is crucial for closed-loop stability.
基金Project of National Social Science Fund of China(Project No.:23BGJ010)。
文摘This study examines the dynamic interplay between the US Dollar Index(USDI)and gold prices(GP)to assess the sustainability of gold price trends.Employing a rolling window bootstrapping causality test methodology across full and sub-samples,the findings of this study challenge the conventional assumption of a stable long-term inverse correlation between USDI and GP,thereby validating the hypothesis that their relationship is nonlinear and time-dependent.During periods of heightened geopolitical and economic volatility,both the US dollar and gold function as safe-haven assets,with USDI fluctuations exerting a positive influence on GP.Conversely,under stable market conditions,the US dollar serves as the currency in which gold is denominated,resulting in a negative impact of USDI on GP.Notably,GP also demonstrates bidirectional causality,exhibiting both positive and negative effects on USDI.The analysis reveals that while a general inverse correlation persists between gold and the US dollar,this relationship transitions to positive during surges in global political and economic instability.In light of contemporary developments—including escalating geopolitical rivalries,tepid post-pandemic economic recovery,and elevated US interest rates driven by inflationary pressures—this study posit that the upward trajectory of gold prices retains a robust empirical foundation.
基金supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions.
文摘This paper establishes a method for identifying and locating dynamic loads in time-varying systems.The proposed method linearizes time-varying parameters within small time units and uses the Wilson-θ inverse analysis method to solve modal loads of each order at each time step.It then uses an exhaustive method to determine the load position.Finally,it calculates the time history of the load.Simulation examples demonstrate how the number of measuring points and step size affect load identi-fication accuracy,verifying that this algorithm achieves good identification accuracy for loads under resonance conditions.Additionally,it explores how noise affects load position and recognition accuracy,while providing a solution.Simulation examples and experimental results demonstrate that the proposed method can identify both the time history and position of loads simultaneously with high identification accuracy.
基金supported in part by the National Key Research and Development Program of China(2022ZD0120001)the National Natural Science Foundation of China(62233004,62273090,62073076)the Jiangsu Provincial Scientific Research Center of Applied Mathematics(BK20233002)
文摘This paper investigates a class of constrained distributed zeroth-order optimization(ZOO) problems over timevarying unbalanced graphs while ensuring privacy preservation among individual agents. Not taking into account recent progress and addressing these concerns separately, there remains a lack of solutions offering theoretical guarantees for both privacy protection and constrained ZOO over time-varying unbalanced graphs.We hereby propose a novel algorithm, termed the differential privacy(DP) distributed push-sum based zeroth-order constrained optimization algorithm(DP-ZOCOA). Operating over time-varying unbalanced graphs, DP-ZOCOA obviates the need for supplemental suboptimization problem computations, thereby reducing overhead in comparison to distributed primary-dual methods. DP-ZOCOA is specifically tailored to tackle constrained ZOO problems over time-varying unbalanced graphs,offering a guarantee of convergence to the optimal solution while robustly preserving privacy. Moreover, we provide rigorous proofs of convergence and privacy for DP-ZOCOA, underscoring its efficacy in attaining optimal convergence without constraints. To enhance its applicability, we incorporate DP-ZOCOA into the federated learning framework and formulate a decentralized zeroth-order constrained federated learning algorithm(ZOCOA-FL) to address challenges stemming from the timevarying imbalance of communication topology. Finally, the performance and effectiveness of the proposed algorithms are thoroughly evaluated through simulations on distributed least squares(DLS) and decentralized federated learning(DFL) tasks.
基金supported in part by the National Natural Science Fundation of China(52225704 and 52107096).
文摘The dynamics of network power response play a crucial role in system stability.However,the integration of power electronic equipment leads to amplitude and angular frequency(abbreviated as"frequency")time-varying characteristics of the node voltage during dynamic processes.As a result,traditional calcu-lation methods for and characteristics of the power response of the network based on phasor and impe-dance lose their validity.Therefore,this paper undertakes mathematical calculations to reveal the power response of a network under excitation by voltage with time-varying amplitude and frequency(TVAF),relying on the original mathematical relationships and superimposed step response.Then,the multi-timescale characteristics of both the active and reactive power of the network are explored physically.Additionally,this paper reveals a new phenomenon of storing and releasing the active and reactive power of the network.To meet practical engineering requirements,a simplified power expression is presented.Finally,the theoretical analysis is validated through time-domain simulations.
基金National Natural Science Foundation of China (10872030)
文摘An eigenaxis maneuver strategy with global robustness is studied for large angle attitude maneuver of rigid spacecraft. A sliding mode attitude control algorithm with an exponential time-varying sliding surface is designed, which guarantees the sliding mode occurrence at the beginning and eliminates the reaching phase of time-invariant sliding mode control. The proposed control law is global robust against matched external disturbances and system uncertainties, and ensures the eigenaxis rotation in the presence of disturbances and parametric uncertainties. The stability of the control law and the existence of global siding mode are proved by Lyapunov method. Furthermore, the system states can be fully predicted by the analytical solution of state equations, which indicates that the attitude error does not exhibit any overshoots and the system has a good dynamic response. A control torque command regulator is introduced to ensure the eigenaxis rotation under the actuator saturation. Finally, a numerical simulation is employed to illustrate the advantages of the proposed control law.
