This article focuses on asymptotic precision motion control for electro-hydraulic axis systems under unknown time-variant parameters,mismatched and matched disturbances.Different from the traditional adaptive results ...This article focuses on asymptotic precision motion control for electro-hydraulic axis systems under unknown time-variant parameters,mismatched and matched disturbances.Different from the traditional adaptive results that are applied to dispose of unknown constant parameters only,the unique feature is that an adaptive-gain nonlinear term is introduced into the control design to handle unknown time-variant parameters.Concurrently both mismatched and matched disturbances existing in electro-hydraulic axis systems can also be addressed in this way.With skillful integration of the backstepping technique and the adaptive control,a synthesized controller framework is successfully developed for electro-hydraulic axis systems,in which the coupled interaction between parameter estimation and disturbance estimation is avoided.Accordingly,this designed controller has the capacity of low-computation costs and simpler parameter tuning when compared to the other ones that integrate the adaptive control and observer/estimator-based technique to dividually handle parameter uncertainties and disturbances.Also,a nonlinear filter is designed to eliminate the“explosion of complexity”issue existing in the classical back-stepping technique.The stability analysis uncovers that all the closed-loop signals are bounded and the asymptotic tracking performance is also assured.Finally,contrastive experiment results validate the superiority of the developed method as well.展开更多
Contrary to conventional design methods that assume uniform and slow temperature changes tied to atmospheric conditions,single-layer spherical reticulated shells undergo significant non-uniform and time-variant temper...Contrary to conventional design methods that assume uniform and slow temperature changes tied to atmospheric conditions,single-layer spherical reticulated shells undergo significant non-uniform and time-variant temperature variations due to dynamic environmental coupling.These differences can affect structural performance and pose safety risks.Here,a systematic numerical method was developed and applied to simulate long-term temperature variations in such a structure under real environmental conditions,revealing its non-uniform distribution characteristics and time-variant regularity.A simplified design method for non-uniform thermal loads,accounting for time-variant environmental factors,was theoretically derived and validated through experiments and simulations.The maximum deviation and mean error rate between calculated and tested results were 6.1℃ and 3.7%,respectively.Calculated temperature fields aligned with simulated ones,with deviations under 6.0℃.Using the design method,non-uniform thermal effects of the structure are analyzed.Maximum member stress and nodal displacement under non-uniform thermal loads reached 119.3 MPa and 19.7 mm,representing increases of 167.5%and 169.9%,respectively,compared to uniform thermal loads.The impacts of healing construction time on non-uniform thermal effects were evaluated,resulting in construction recommendations.The methodologies and conclusions presented here can serve as valuable references for the thermal design,construction,and control of single-layer spherical reticulated shells or similar structures.展开更多
Assessment of imprecise time-variant reliability in engineering is a critical task when accounting for both the variability of structural properties and loads over time and the presence of uncertainties involved in th...Assessment of imprecise time-variant reliability in engineering is a critical task when accounting for both the variability of structural properties and loads over time and the presence of uncertainties involved in the ambiguity of parameters simultaneously.To estimate the Imprecise Time-variant Failure Probability Function(ITFPF)and derive the imprecise reliability results as a byproduct,Adaptive Combination Augmented Line Sampling(ACALS)is proposed.It consists of three integrated features:Augmented Line Sampling(ALS),adaptive strategy,and the optimal combination.ALS is adopted as an efficient analysis tool to obtain the failure probability function w.r.t.imprecise parameters.Then,the adaptive strategy iteratively applies ALS while considering both imprecise parameters and time simultaneously.Finally,the optimal combination algorithm collects all result components in an optimal manner to minimize the Coefficient of Variance(C.o.V.)of the ITFPF estimate.Overall,the proposed ACALS method outperforms the original ALS method by efficiently estimating the ITFPF while guaranteeing a minimal C.o.V.Thus,the proposed approach can serve as an effective tool for imprecise time-variant reliability analysis in real engineering applications.Several examples are presented to demonstrate the superiority of the proposed approach in addressing the challenges of estimating the ITFPF.展开更多
Studying the seasonal deformation in GPS time series is important to interpreting geophysical contributors and identifying unmodeled and mismodeled seasonal signals.Traditional seasonal signal extraction used the leas...Studying the seasonal deformation in GPS time series is important to interpreting geophysical contributors and identifying unmodeled and mismodeled seasonal signals.Traditional seasonal signal extraction used the least squares method,which models seasonal deformation as a constant seasonal amplitude and phase.However,the seasonal variations are not constant from year to year,and the seasonal amplitude and phase are time-variable.In order to obtain the time-variable seasonal signal in the GPS station coordinate time series,singular spectrum analysis(SSA)is conducted in this study.We firstly applied the SSA on simulated seasonal signals with different frequencies 1.00 cycle per year(cpy),1.04 cpy and with time-variable amplitude are superimposed.It was found that SSA can successfully obtain the seasonal variations with different frequencies and with time-variable amplitude superimposed.Then,SSA is carried out on the GPS observations in Yunnan Province.The results show that the time-variable amplitude seasonal signals are ubiquitous in Yunnan Province,and the timevariable amplitude change in 2019 in the region is extracted,which is further explained by the soil moisture mass loading and atmospheric pressure loading.After removing the two loading effects,the SSA obtained modulated seasonal signals which contain the obvious seasonal variations at frequency of 1.046 cpy,it is close with the GPS draconitic year,1.040 cpy.Hence,the time-variable amplitude changes in 2019 and the seasonal GPS draconitic year in the region could be discriminated successfully by SSA in Yunnan Province.展开更多
In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems...In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.展开更多
Zeroing neural dynamic(ZND)model is widely deployed for time-variant non-linear equations(TVNE).Various element-wise non-linear activation functions and integration operations are investigated to enhance the convergen...Zeroing neural dynamic(ZND)model is widely deployed for time-variant non-linear equations(TVNE).Various element-wise non-linear activation functions and integration operations are investigated to enhance the convergence performance and robustness in most proposed ZND models for solving TVNE,leading to a huge cost of hardware implementation and model complexity.To overcome these problems,the authors develop a new norm-based ZND(NBZND)model with strong robustness for solving TVNE,not applying element-wise non-linear activated functions but introducing a two-norm operation to achieve finite-time convergence.Moreover,the authors develop a discretetime NBZND model for the potential deployment of the model on digital computers.Rigorous theoretical analysis for the NBZND is provided.Simulation results substantiate the advantages of the NBZND model for solving TVNE.展开更多
During the past few decades, it has become clear that the distribution, sizes, and masses of cosmic structures are best described as fractal rather than homogeneous. This means that an entirely different formalism is ...During the past few decades, it has become clear that the distribution, sizes, and masses of cosmic structures are best described as fractal rather than homogeneous. This means that an entirely different formalism is needed to replace the standard perturbation model of structure formation. Recently, we have been developing a model of cosmology that accounts for a large number of the observed properties of the universe. A key component of this model is that fractal structures that later regulated the creation of both matter and radiation came into existence during the initial Planck-era inflation. Initially, the vacuum was the only existence and since time, distance, and energy were uncertain, its only property, the curvature (or energy), was most likely distributed randomly. Everything that happened after the Planck era can be described by the known laws of physics so the remaining fundamental problem is to discover how such a random beginning could organize itself into the hierarchy of highly non-random self-similar structures on all length scales that are necessary to explain the existence of all cosmic structures. In this paper, we present a variation of the standard sandpile model that points to a solution. Incidental to our review of the distributions of cosmic structures, we discovered that the apparent transition from a fractal to a homogeneous distribution of structures at a distance of about 150 Mpc is a consequence of the finite size of the universe rather than a change in the underlying statistics of the distributions.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
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 investigates the problem of cluster synchronization of master-slave complex net-works with time-varying delay via linear and adaptive feedback pinning controls.We need not non-delayed and delayed coupling m...This paper investigates the problem of cluster synchronization of master-slave complex net-works with time-varying delay via linear and adaptive feedback pinning controls.We need not non-delayed and delayed coupling matrices to be symmetric or irreducible.We have the advantages of using adaptive control method to reduce control gain and pinning control technology to reduce cost.By con-structing Lyapunov function,some sufficient synchronization criteria are established.Finally,numerical examples are employed to illustrate the effectiveness of the proposed approach.展开更多
This paper addresses the computational problem of fixed-interval smoothing state estimation in linear time-varying Gaussian stochastic systems.A new fixed-interval Kalman smoothing algorithm is proposed,and the corres...This paper addresses the computational problem of fixed-interval smoothing state estimation in linear time-varying Gaussian stochastic systems.A new fixed-interval Kalman smoothing algorithm is proposed,and the corresponding form of the smoother is derived.The method is able to accommodate situations where process and measurement noises are correlated,a limitation often encountered in conventional approaches.The Kalman smoothing problem discussed in this paper can be reformulated as an equivalent constrained optimization problem,where the solution corresponds to a set of linear equations defined by a specific co-efficient matrix.Through multiple permutations,the co-efficient matrix of linear equations is transformed into a block tridiagonal form,and then both sides of the linear system are multiplied by the inverse of the co-efficient matrix.This approach is based on the transformation of linear systems described in the SPIKE algorithm and is particularly well-suited for large-scale sparse block tridiagonal matrix structures.It enables efficient,parallel,and flexible solutions while maintaining a certain degree of block diagonal dominance.Compared to directly solving block tridiagonal co-efficient matrices,this method demonstrates appreciable advantages in terms of numerical stability and computational efficiency.Consequently,the new smoothing algorithm yields a new smoother that features fewer constraints and broader applicability than traditional methods.The estimates,such as smoothed state,covariance,and cross-covariance,are essential for fields,such as system identification,navigation,guidance,and control.Finally,the effectiveness of the proposed smoothing algorithm and smoother is validated through numerical simulations.展开更多
The present study develops a data-based compact model for the prediction of the fluid temperature evolution in district heating-and-cooling pipeline networks.This model is based on an existing“reduced-order model”by...The present study develops a data-based compact model for the prediction of the fluid temperature evolution in district heating-and-cooling pipeline networks.This model is based on an existing“reduced-order model”by the authors obtained from reduction of the“full-order model”describing the spatio-temporal energy balance for each pipe segment to a semi-analytical input-output relation between the pipe outlet temperature and the pipe inlet and ground temperatures.The proposed model(denoted XROM)expands on the original reduced-order model by incorporating variable mass flux as an additional input and thus greatly increases its practical relevance.The XROM represents variable mass flux by step-wise switching between mass-flux levels and thereby induces a prediction error relative to the true full-order model evolution after each switching.Theoretical analysis rigorously demonstrates that this error always decays and the XROM invariably converges on the full-order model evolution and,consequently,affords the same prediction accuracy.Performance analyses reveal that prediction errors are restricted to short“convergence intervals”after each mass-flux switching and the XROM therefore can handle substantially faster operating schemes than the current ones based on hourly monitoring and control.Convergence intervals of O(minutes)are namely typically sufficient-and thus switching frequencies up to O(minutes 1)permissible during dynamic operation and control actions-for reliable predictions.Quantification of these convergence intervals by an easy-to-use empirical relation furthermore enables a priori determination of the conditions for reliable predictions.Moreover,the XROM can capture the full 3D system dynamics(provided incompressible flow and heat-transfer mechanisms depending linearly on temperature)versus the essentially 1D approximation of current compact pipe models yet at similar computational cost.These attributes advance(parts of)district heating and cooling networks demanding prediction accuracies beyond 1D as its primary application area.This makes the XROM complementary to said pipe models and thereby expands the modelling capabilities for handling the growing complexity of(next-generation)networks.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
This paper investigates the cooperative tracking control problem of Electromagnetic Formation Spacecraft(EMFS)on elliptical orbit.The actuator saturation and topology switching problems exist in formation cooperative ...This paper investigates the cooperative tracking control problem of Electromagnetic Formation Spacecraft(EMFS)on elliptical orbit.The actuator saturation and topology switching problems exist in formation cooperative tracking control.The proposed novel adaptive consensus protocol addresses this problem by utilizing both synchronous and asynchronous topology switching.Firstly,to enhance the robustness of the system and minimize the impact of time-varying parameters on the control algorithm,the controller gain is determined through solving the Adaptive Riccati Differential Equation(ARDE).Secondly,a three-layer network communication structure with mirror nodes is constructed,in which different control input saturation levels are designed according to the correlation with the leader.Then,the Average Dwell Time(ADT)switching technique is utilized to generate the control switching signal,ensuring that the topology maintains a directed spanning tree when the switching signal condition is satisfied.Finally,simulation results validate the theoretical findings and provide a comparison with other methods,demonstrating the superiority of the proposed approach.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
In the Satellite-integrated Internet of Things(S-IoT),data freshness in the time-sensitive scenarios could not be guaranteed over the timevarying topology with current distribution strategies aiming to reduce the tran...In the Satellite-integrated Internet of Things(S-IoT),data freshness in the time-sensitive scenarios could not be guaranteed over the timevarying topology with current distribution strategies aiming to reduce the transmission delay.To address this problem,in this paper,we propose an age-optimal caching distribution mechanism for the high-timeliness data collection in S-IoT by adopting a freshness metric,as called age of information(AoI)through the caching-based single-source multidestinations(SSMDs)transmission,namely Multi-AoI,with a well-designed cross-slot directed graph(CSG).With the proposed CSG,we make optimizations on the locations of cache nodes by solving a nonlinear integer programming problem on minimizing Multi-AoI.In particular,we put up forward three specific algorithms respectively for improving the Multi-AoI,i.e.,the minimum queuing delay algorithm(MQDA)based on node deviation from average level,the minimum propagation delay algorithm(MPDA)based on the node propagation delay reduction,and a delay balanced algorithm(DBA)based on node deviation from average level and propagation delay reduction.The simulation results show that the proposed mechanism can effectively improve the freshness of information compared with the random selection algorithm.展开更多
Tooth cracks may occur in spiral bevel gear transmission system of the aerospace equipment.In this study,an accurate and efficient loaded tooth contact analysis(LTCA)model is developed to predict the contact behavior ...Tooth cracks may occur in spiral bevel gear transmission system of the aerospace equipment.In this study,an accurate and efficient loaded tooth contact analysis(LTCA)model is developed to predict the contact behavior and time-varying meshing stiffness(TVMS)of spiral bevel gear pair with cracked tooth.The tooth is sliced,and the contact points on slices are computed using roll angle surfaces.Considering the geometric complexity of crack surface,a set of procedures is formulated to generate spatial crack and determine crack parameters for contact points.According to the positional relationship between contact point and crack path,each sliced tooth is modeled as a non-uniform cantilever beam with varying reduced effective load-bearing tooth thickness.Then the compliance model of the cracked tooth is established to perform contact analysis,along with TVMS calculations utilizing three different models.By employing spiral bevel gear pairs with distinct types of cracks as examples,the accuracy and efficiency of the developed approach are validated via comparative analyses with finite element analysis(FEA)outcomes.Furthermore,the investigation on effects of cracks shows that tooth cracks can induce alterations in meshing performance of both entire gear pair and individual tooth pairs,including not only cracked tooth pair but also adjacent non-cracked tooth pairs.Hence,the proposed model can serve as a useful tool for analyzing the variations in contact behavior and meshing stiffness of spiral bevel gears due to different cracks.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
In the existing impact time control guidance (ITCG) laws for moving-targets, the effects of time-varying velocity caused by aerodynamics and gravity cannot be effectively con-sidered. Therefore, an ITCG with field-of-...In the existing impact time control guidance (ITCG) laws for moving-targets, the effects of time-varying velocity caused by aerodynamics and gravity cannot be effectively con-sidered. Therefore, an ITCG with field-of-view (FOV) constraints based on biased proportional navigation guidance (PNG) is developed in this paper. The remaining flight time (time-to-go) estimation method is derived considering aerodynamic force and gravity. The number of differential equations is reduced and the integration step is increased by changing the integral variable, which makes it possible to obtain time-to-go through integration. An impact time controller with FOV constraints is proposed by analyzing the influence of the biased term on time-to-go and FOV constraint. Then, numerical simulations are performed to verify the correctness and superiority of the method.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
基金supported in part by the National Key R&D Program of China(No.2021YFB2011300)the National Natural Science Foundation of China(No.52075262,51905271,52275062)+1 种基金the Fok Ying-Tong Education Foundation of China(No.171044)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX22_0471)。
文摘This article focuses on asymptotic precision motion control for electro-hydraulic axis systems under unknown time-variant parameters,mismatched and matched disturbances.Different from the traditional adaptive results that are applied to dispose of unknown constant parameters only,the unique feature is that an adaptive-gain nonlinear term is introduced into the control design to handle unknown time-variant parameters.Concurrently both mismatched and matched disturbances existing in electro-hydraulic axis systems can also be addressed in this way.With skillful integration of the backstepping technique and the adaptive control,a synthesized controller framework is successfully developed for electro-hydraulic axis systems,in which the coupled interaction between parameter estimation and disturbance estimation is avoided.Accordingly,this designed controller has the capacity of low-computation costs and simpler parameter tuning when compared to the other ones that integrate the adaptive control and observer/estimator-based technique to dividually handle parameter uncertainties and disturbances.Also,a nonlinear filter is designed to eliminate the“explosion of complexity”issue existing in the classical back-stepping technique.The stability analysis uncovers that all the closed-loop signals are bounded and the asymptotic tracking performance is also assured.Finally,contrastive experiment results validate the superiority of the developed method as well.
基金This work is supported by the National Natural Science Foundation of China(Nos.51578491 and 52238001).
文摘Contrary to conventional design methods that assume uniform and slow temperature changes tied to atmospheric conditions,single-layer spherical reticulated shells undergo significant non-uniform and time-variant temperature variations due to dynamic environmental coupling.These differences can affect structural performance and pose safety risks.Here,a systematic numerical method was developed and applied to simulate long-term temperature variations in such a structure under real environmental conditions,revealing its non-uniform distribution characteristics and time-variant regularity.A simplified design method for non-uniform thermal loads,accounting for time-variant environmental factors,was theoretically derived and validated through experiments and simulations.The maximum deviation and mean error rate between calculated and tested results were 6.1℃ and 3.7%,respectively.Calculated temperature fields aligned with simulated ones,with deviations under 6.0℃.Using the design method,non-uniform thermal effects of the structure are analyzed.Maximum member stress and nodal displacement under non-uniform thermal loads reached 119.3 MPa and 19.7 mm,representing increases of 167.5%and 169.9%,respectively,compared to uniform thermal loads.The impacts of healing construction time on non-uniform thermal effects were evaluated,resulting in construction recommendations.The methodologies and conclusions presented here can serve as valuable references for the thermal design,construction,and control of single-layer spherical reticulated shells or similar structures.
基金The Aeronautical Science Foundation of China(Nos.20170968002,20230003068002)The National Major Science and Technology Projects of China(Nos.J2019-II-0022-0043,J2019-VII-0013-0153).
文摘Assessment of imprecise time-variant reliability in engineering is a critical task when accounting for both the variability of structural properties and loads over time and the presence of uncertainties involved in the ambiguity of parameters simultaneously.To estimate the Imprecise Time-variant Failure Probability Function(ITFPF)and derive the imprecise reliability results as a byproduct,Adaptive Combination Augmented Line Sampling(ACALS)is proposed.It consists of three integrated features:Augmented Line Sampling(ALS),adaptive strategy,and the optimal combination.ALS is adopted as an efficient analysis tool to obtain the failure probability function w.r.t.imprecise parameters.Then,the adaptive strategy iteratively applies ALS while considering both imprecise parameters and time simultaneously.Finally,the optimal combination algorithm collects all result components in an optimal manner to minimize the Coefficient of Variance(C.o.V.)of the ITFPF estimate.Overall,the proposed ACALS method outperforms the original ALS method by efficiently estimating the ITFPF while guaranteeing a minimal C.o.V.Thus,the proposed approach can serve as an effective tool for imprecise time-variant reliability analysis in real engineering applications.Several examples are presented to demonstrate the superiority of the proposed approach in addressing the challenges of estimating the ITFPF.
基金funded by National Natural Science Foundation of China(Grant No.11803065)Natural Science Foundation of Shanghai(Grant No.22ZR1472800)。
文摘Studying the seasonal deformation in GPS time series is important to interpreting geophysical contributors and identifying unmodeled and mismodeled seasonal signals.Traditional seasonal signal extraction used the least squares method,which models seasonal deformation as a constant seasonal amplitude and phase.However,the seasonal variations are not constant from year to year,and the seasonal amplitude and phase are time-variable.In order to obtain the time-variable seasonal signal in the GPS station coordinate time series,singular spectrum analysis(SSA)is conducted in this study.We firstly applied the SSA on simulated seasonal signals with different frequencies 1.00 cycle per year(cpy),1.04 cpy and with time-variable amplitude are superimposed.It was found that SSA can successfully obtain the seasonal variations with different frequencies and with time-variable amplitude superimposed.Then,SSA is carried out on the GPS observations in Yunnan Province.The results show that the time-variable amplitude seasonal signals are ubiquitous in Yunnan Province,and the timevariable amplitude change in 2019 in the region is extracted,which is further explained by the soil moisture mass loading and atmospheric pressure loading.After removing the two loading effects,the SSA obtained modulated seasonal signals which contain the obvious seasonal variations at frequency of 1.046 cpy,it is close with the GPS draconitic year,1.040 cpy.Hence,the time-variable amplitude changes in 2019 and the seasonal GPS draconitic year in the region could be discriminated successfully by SSA in Yunnan Province.
基金partially supported by the National Natural Science Foundation of China(52375238)Science and Technology Program of Guangzhou(202201020213,202201020193,202201010399)GZHU-HKUST Joint Research Fund(YH202109).
文摘In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.
基金Natural Science Foundation of China,Grant/Award Number:62206109Guangdong Basic and Applied Basic Research Foundation,Grant/Award Number:2022A1515010976+1 种基金Young Scholar Program of Pazhou Lab,Grant/Award Number:PZL2021KF0022National College Student Innovation and Entrepreneurship Training Program,Grant/Award Number:202410559070。
文摘Zeroing neural dynamic(ZND)model is widely deployed for time-variant non-linear equations(TVNE).Various element-wise non-linear activation functions and integration operations are investigated to enhance the convergence performance and robustness in most proposed ZND models for solving TVNE,leading to a huge cost of hardware implementation and model complexity.To overcome these problems,the authors develop a new norm-based ZND(NBZND)model with strong robustness for solving TVNE,not applying element-wise non-linear activated functions but introducing a two-norm operation to achieve finite-time convergence.Moreover,the authors develop a discretetime NBZND model for the potential deployment of the model on digital computers.Rigorous theoretical analysis for the NBZND is provided.Simulation results substantiate the advantages of the NBZND model for solving TVNE.
文摘During the past few decades, it has become clear that the distribution, sizes, and masses of cosmic structures are best described as fractal rather than homogeneous. This means that an entirely different formalism is needed to replace the standard perturbation model of structure formation. Recently, we have been developing a model of cosmology that accounts for a large number of the observed properties of the universe. A key component of this model is that fractal structures that later regulated the creation of both matter and radiation came into existence during the initial Planck-era inflation. Initially, the vacuum was the only existence and since time, distance, and energy were uncertain, its only property, the curvature (or energy), was most likely distributed randomly. Everything that happened after the Planck era can be described by the known laws of physics so the remaining fundamental problem is to discover how such a random beginning could organize itself into the hierarchy of highly non-random self-similar structures on all length scales that are necessary to explain the existence of all cosmic structures. In this paper, we present a variation of the standard sandpile model that points to a solution. Incidental to our review of the distributions of cosmic structures, we discovered that the apparent transition from a fractal to a homogeneous distribution of structures at a distance of about 150 Mpc is a consequence of the finite size of the universe rather than a change in the underlying statistics of the distributions.
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.
文摘This paper investigates the problem of cluster synchronization of master-slave complex net-works with time-varying delay via linear and adaptive feedback pinning controls.We need not non-delayed and delayed coupling matrices to be symmetric or irreducible.We have the advantages of using adaptive control method to reduce control gain and pinning control technology to reduce cost.By con-structing Lyapunov function,some sufficient synchronization criteria are established.Finally,numerical examples are employed to illustrate the effectiveness of the proposed approach.
文摘This paper addresses the computational problem of fixed-interval smoothing state estimation in linear time-varying Gaussian stochastic systems.A new fixed-interval Kalman smoothing algorithm is proposed,and the corresponding form of the smoother is derived.The method is able to accommodate situations where process and measurement noises are correlated,a limitation often encountered in conventional approaches.The Kalman smoothing problem discussed in this paper can be reformulated as an equivalent constrained optimization problem,where the solution corresponds to a set of linear equations defined by a specific co-efficient matrix.Through multiple permutations,the co-efficient matrix of linear equations is transformed into a block tridiagonal form,and then both sides of the linear system are multiplied by the inverse of the co-efficient matrix.This approach is based on the transformation of linear systems described in the SPIKE algorithm and is particularly well-suited for large-scale sparse block tridiagonal matrix structures.It enables efficient,parallel,and flexible solutions while maintaining a certain degree of block diagonal dominance.Compared to directly solving block tridiagonal co-efficient matrices,this method demonstrates appreciable advantages in terms of numerical stability and computational efficiency.Consequently,the new smoothing algorithm yields a new smoother that features fewer constraints and broader applicability than traditional methods.The estimates,such as smoothed state,covariance,and cross-covariance,are essential for fields,such as system identification,navigation,guidance,and control.Finally,the effectiveness of the proposed smoothing algorithm and smoother is validated through numerical simulations.
文摘The present study develops a data-based compact model for the prediction of the fluid temperature evolution in district heating-and-cooling pipeline networks.This model is based on an existing“reduced-order model”by the authors obtained from reduction of the“full-order model”describing the spatio-temporal energy balance for each pipe segment to a semi-analytical input-output relation between the pipe outlet temperature and the pipe inlet and ground temperatures.The proposed model(denoted XROM)expands on the original reduced-order model by incorporating variable mass flux as an additional input and thus greatly increases its practical relevance.The XROM represents variable mass flux by step-wise switching between mass-flux levels and thereby induces a prediction error relative to the true full-order model evolution after each switching.Theoretical analysis rigorously demonstrates that this error always decays and the XROM invariably converges on the full-order model evolution and,consequently,affords the same prediction accuracy.Performance analyses reveal that prediction errors are restricted to short“convergence intervals”after each mass-flux switching and the XROM therefore can handle substantially faster operating schemes than the current ones based on hourly monitoring and control.Convergence intervals of O(minutes)are namely typically sufficient-and thus switching frequencies up to O(minutes 1)permissible during dynamic operation and control actions-for reliable predictions.Quantification of these convergence intervals by an easy-to-use empirical relation furthermore enables a priori determination of the conditions for reliable predictions.Moreover,the XROM can capture the full 3D system dynamics(provided incompressible flow and heat-transfer mechanisms depending linearly on temperature)versus the essentially 1D approximation of current compact pipe models yet at similar computational cost.These attributes advance(parts of)district heating and cooling networks demanding prediction accuracies beyond 1D as its primary application area.This makes the XROM complementary to said pipe models and thereby expands the modelling capabilities for handling the growing complexity of(next-generation)networks.
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 National Natural Science Foundation of China(No.6200326)。
文摘This paper investigates the cooperative tracking control problem of Electromagnetic Formation Spacecraft(EMFS)on elliptical orbit.The actuator saturation and topology switching problems exist in formation cooperative tracking control.The proposed novel adaptive consensus protocol addresses this problem by utilizing both synchronous and asynchronous topology switching.Firstly,to enhance the robustness of the system and minimize the impact of time-varying parameters on the control algorithm,the controller gain is determined through solving the Adaptive Riccati Differential Equation(ARDE).Secondly,a three-layer network communication structure with mirror nodes is constructed,in which different control input saturation levels are designed according to the correlation with the leader.Then,the Average Dwell Time(ADT)switching technique is utilized to generate the control switching signal,ensuring that the topology maintains a directed spanning tree when the switching signal condition is satisfied.Finally,simulation results validate the theoretical findings and provide a comparison with other methods,demonstrating the superiority of the proposed approach.
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supports from the Major Key Project of PCL (PCL2021A031)Shenzhen Science Technology Program (GXWD20201230155427003-20200824093323001)
文摘In the Satellite-integrated Internet of Things(S-IoT),data freshness in the time-sensitive scenarios could not be guaranteed over the timevarying topology with current distribution strategies aiming to reduce the transmission delay.To address this problem,in this paper,we propose an age-optimal caching distribution mechanism for the high-timeliness data collection in S-IoT by adopting a freshness metric,as called age of information(AoI)through the caching-based single-source multidestinations(SSMDs)transmission,namely Multi-AoI,with a well-designed cross-slot directed graph(CSG).With the proposed CSG,we make optimizations on the locations of cache nodes by solving a nonlinear integer programming problem on minimizing Multi-AoI.In particular,we put up forward three specific algorithms respectively for improving the Multi-AoI,i.e.,the minimum queuing delay algorithm(MQDA)based on node deviation from average level,the minimum propagation delay algorithm(MPDA)based on the node propagation delay reduction,and a delay balanced algorithm(DBA)based on node deviation from average level and propagation delay reduction.The simulation results show that the proposed mechanism can effectively improve the freshness of information compared with the random selection algorithm.
基金co-supported by the National Natural Science Foundation of China (No. 52175104)the Postdoctoral Fellowship Program of CPSF (No. GZC20233008)
文摘Tooth cracks may occur in spiral bevel gear transmission system of the aerospace equipment.In this study,an accurate and efficient loaded tooth contact analysis(LTCA)model is developed to predict the contact behavior and time-varying meshing stiffness(TVMS)of spiral bevel gear pair with cracked tooth.The tooth is sliced,and the contact points on slices are computed using roll angle surfaces.Considering the geometric complexity of crack surface,a set of procedures is formulated to generate spatial crack and determine crack parameters for contact points.According to the positional relationship between contact point and crack path,each sliced tooth is modeled as a non-uniform cantilever beam with varying reduced effective load-bearing tooth thickness.Then the compliance model of the cracked tooth is established to perform contact analysis,along with TVMS calculations utilizing three different models.By employing spiral bevel gear pairs with distinct types of cracks as examples,the accuracy and efficiency of the developed approach are validated via comparative analyses with finite element analysis(FEA)outcomes.Furthermore,the investigation on effects of cracks shows that tooth cracks can induce alterations in meshing performance of both entire gear pair and individual tooth pairs,including not only cracked tooth pair but also adjacent non-cracked tooth pairs.Hence,the proposed model can serve as a useful tool for analyzing the variations in contact behavior and meshing stiffness of spiral bevel gears due to different cracks.
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 by the National Natural Science Foundation of China(U21B2028).
文摘In the existing impact time control guidance (ITCG) laws for moving-targets, the effects of time-varying velocity caused by aerodynamics and gravity cannot be effectively con-sidered. Therefore, an ITCG with field-of-view (FOV) constraints based on biased proportional navigation guidance (PNG) is developed in this paper. The remaining flight time (time-to-go) estimation method is derived considering aerodynamic force and gravity. The number of differential equations is reduced and the integration step is increased by changing the integral variable, which makes it possible to obtain time-to-go through integration. An impact time controller with FOV constraints is proposed by analyzing the influence of the biased term on time-to-go and FOV constraint. Then, numerical simulations are performed to verify the correctness and superiority of the method.
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.
