In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation ...In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method.展开更多
A new decentralized robust control method is discussed for a class of nonlinear interconnected largescale system with unknown bounded disturbance and unknown nonlinear function term. A decentralized control law is pro...A new decentralized robust control method is discussed for a class of nonlinear interconnected largescale system with unknown bounded disturbance and unknown nonlinear function term. A decentralized control law is proposed which combines the approximation method of neural network with sliding mode control. The decentralized controller consists of an equivalent controller and an adaptive sliding mode controller. The sliding mode controller is a robust controller used to reduce the track error of the control system. The neural networks are used to approximate the unknown nonlinear functions, meanwhile the approximation errors of the neural networks are applied to the weight value updated law to improve performance of the system. Finally, an example demonstrates the availability of the decentralized control method.展开更多
We study the correlation between detrended fluctuation analysis（DFA） and the Lempel-Ziv complexity（LZC） in nonlinear time series analysis in this paper.Typical dynamic systems including a logistic map and a Duffin...We study the correlation between detrended fluctuation analysis（DFA） and the Lempel-Ziv complexity（LZC） in nonlinear time series analysis in this paper.Typical dynamic systems including a logistic map and a Duffing model are investigated.Moreover,the influence of Gaussian random noise on both the DFA and LZC are analyzed.The results show a high correlation between the DFA and LZC,which can quantify the non-stationarity and the nonlinearity of the time series,respectively.With the enhancement of the random component,the exponent α and the normalized complexity index C show increasing trends.In addition,C is found to be more sensitive to the fluctuation in the nonlinear time series than α.Finally,the correlation between the DFA and LZC is applied to the extraction of vibration signals for a reciprocating compressor gas valve,and an effective fault diagnosis result is obtained.展开更多
The compact implicit integration factor （cIIF） method is an efficient time discretization scheme for stiff nonlinear diffusion equations in two and three spatial dimensions. In the current work, we apply the cIIF me...The compact implicit integration factor （cIIF） method is an efficient time discretization scheme for stiff nonlinear diffusion equations in two and three spatial dimensions. In the current work, we apply the cIIF method to some complex-valued nonlinear evolutionary equations such as the nonlinear SchrSdinger （NLS） equation and the complex Ginzburg-Landau （GL） equation. Detailed algorithm formulation and practical implementation of cIIF method are performed. The numerical results indicate that this method is very accurate and efficient.展开更多
This paper deals with a nonlinear boundary value problem for a complex equation W_z = H(Z,W,W_z),Z ∈G : |Z|<1 with boundary eondition of the form I.l-i Re[Z-W(Z)] = ψ(Z,W(Z)) + Re[λ_0+sum from k=1 to |n|-1(λ_k ...This paper deals with a nonlinear boundary value problem for a complex equation W_z = H(Z,W,W_z),Z ∈G : |Z|<1 with boundary eondition of the form I.l-i Re[Z-W(Z)] = ψ(Z,W(Z)) + Re[λ_0+sum from k=1 to |n|-1(λ_k + iλ_k)Z^k],Z∈Γ:|z|=1 k--1 in which the index is negative. By establishing a priori estimate and using the imbdding method combined with the the Newton interation procedure, it is proved that the above problem is solvable and the solution is unique in C^l+a(g) ,O<a<].展开更多
Accurately solving transient nonlinear inverse heat conduction problems in complex structures is of great importance to provide key parameters for modeling coupled heat transfer process and the structure’s optimizati...Accurately solving transient nonlinear inverse heat conduction problems in complex structures is of great importance to provide key parameters for modeling coupled heat transfer process and the structure’s optimization design.The finite element method in ABAQUS is employed to solve the direct transient nonlinear heat conduction problem.Improved particle swarm optimization(PSO)method is developed and used to solve the transient nonlinear inverse problem.To investigate the inverse performances,some numerical tests are provided.Boundary conditions at inaccessible surfaces of a scramjet combustor with the regenerative cooling system are inversely identified.The results show that the new methodology can accurately and efficiently determine the boundary conditions in the scramjet combustor with the regenerative cooling system.By solving the transient nonlinear inverse problem,the improved particle swarm optimization for solving the transient nonlinear inverse heat conduction problem in a complex structure is verified.展开更多
We investigate the impulsive synchronization of a nonlinear coupled complex network with a delay node. Both delay coupling and non-delay coupling, as well as the symmetrical coupling matrix and the asymmetrical coupli...We investigate the impulsive synchronization of a nonlinear coupled complex network with a delay node. Both delay coupling and non-delay coupling, as well as the symmetrical coupling matrix and the asymmetrical coupling matrix are considered. Based on the comparison theorem of an impulsive differential system, some novel synchronization criteria are derived. Finally, numerical simulations demonstrate the effectiveness of the proposed synchronization criteria.展开更多
Cylindrical and spherical dust-electron-acoustic （DEA） shock waves and double layers in an unmagnetized, col- lisionless, complex or dusty plasma system are carried out. The plasma system is assumed to be composed o...Cylindrical and spherical dust-electron-acoustic （DEA） shock waves and double layers in an unmagnetized, col- lisionless, complex or dusty plasma system are carried out. The plasma system is assumed to be composed of inertial and viscous cold electron fluids, nonextensive distributed hot electrons, Maxwellian ions, and negatively charged stationary dust grains. The standard reductive perturbation technique is used to derive the nonlinear dynamical equations, that is, the nonplanar Burgers equation and the nonplanar further Burgers equation. They are also numerically analyzed to investigate the basic features of shock waves and double layers （DLs）. It is observed that the roles of the viscous cold electron fluids, nonextensivity of hot electrons, and other plasma parameters in this investigation have significantly modified the basic features （such as, polarity, amplitude and width） of the nonplanar DEA shock waves and DLs. It is also observed that the strength of the shock is maximal for the spherical geometry, intermediate for cylindrical geometry, while it is minimal for the planar geometry. The findings of our results obtained from this theoretical investigation may be useful in understanding the nonlinear phenomena associated with the nonplanar DEA waves in both space and laboratory plasmas.展开更多
Duality analysis of time series and complex networks has been a frontier topic during the last several decades.According to some recent approaches in this direction,the intrinsic dynamics of typical nonlinear systems ...Duality analysis of time series and complex networks has been a frontier topic during the last several decades.According to some recent approaches in this direction,the intrinsic dynamics of typical nonlinear systems can be better characterized by considering the related nonlinear time series from the perspective of networks science.In this paper,the associated network family of the unified piecewise-linear(PWL)chaotic family,which can bridge the gap of the PWL chaotic Lorenz system and the PWL chaotic Chen system,was firstly constructed and analyzed.We constructed the associated network family via the original and the modified frequency-degree mapping strategy,as well as the classical visibility graph and horizontal visibility graph strategy,after removing the transient states.Typical related network characteristics,including the network fractal dimension,of the associated network family,are computed with changes of single key parameter a.These characteristic vectors of the network are also compared with the largest Lyapunov exponent(LLE)vector of the related original dynamical system.It can be found that,some network characteristics are highly correlated with LLE vector of the original nonlinear system,i.e.,there is an internal consistency between the largest Lyapunov exponents,some typical associated network characteristics,and the related network fractal dimension index.Numerical results show that the modified frequency-degree mapping strategy can demonstrate highest correlation,which means it can behave better to capture the intrinsic characteristics of the unified PWL chaotic family.展开更多
Complex networks have established themselves in recent years as being particularly suitable and flexible for representing and modelling many complex natural and artificial systems. Oil-water two-phase flow is one of t...Complex networks have established themselves in recent years as being particularly suitable and flexible for representing and modelling many complex natural and artificial systems. Oil-water two-phase flow is one of the most complex systems. In this paper, we use complex networks to study the inclined oil water two-phase flow. Two different complex network construction methods are proposed to build two types of networks, i.e. the flow pattern complex network （FPCN） and fluid dynamic complex network （FDCN）. Through detecting the community structure of FPCN by the community-detection algorithm based on K-means clustering, useful and interesting results are found which can be used for identifying three inclined oil-water flow patterns. To investigate the dynamic characteristics of the inclined oil-water two-phase flow, we construct 48 FDCNs under different flow conditions, and find that the power-law exponent and the network information entropy, which are sensitive to the flow pattern transition, can both characterize the nonlinear dynamics of the inclined oil-water two-phase flow. In this paper, from a new perspective, we not only introduce a complex network theory into the study of the oil-water two-phase flow but also indicate that the complex network may be a powerful tool for exploring nonlinear time series in practice.展开更多
The uneven spatial distribution of stations providing precipitable water vapor(PWV)observations in China hinders the effective use of these data in assimilation,nowcasting,and prediction.In this study,we proposed a co...The uneven spatial distribution of stations providing precipitable water vapor(PWV)observations in China hinders the effective use of these data in assimilation,nowcasting,and prediction.In this study,we proposed a complex network framework for exploring the topological structure and the collective behavior of PWV in the mainland of China.We used the Pearson correlation coefficient and transfer entropy to measure the linear and nonlinear relationships of PWV amongst different stations and to set up the undirected and directed complex networks,respectively.Our findings revealed the statistical and geographical distribution of the variables influencing PWV networks and identified the vapor information source and sink stations.Specifically,the findings showed that the statistical and spatial distributions of the undirected and directed complex vapor networks in terms of degree and distance were similar to each other(the common interaction mode for vapor stations and their locations).The betweenness results displayed different features.The largest betweenness ratio for directed networks tended to be larger than that of the undirected networks,implying that the transfer of directed PWV networks was more efficient than that of the undirected networks.The findings of this study are heuristic and will be useful for constructing the best strategy for the PWV data in applications such as vapor observational networks design and precipitation prediction.展开更多
We introduce a new integral scheme namely improved Kudryashov method for solving any nonlinear fractional differential model.Specifically,we apply the approach to the nonlinear space-time fractional model leading the ...We introduce a new integral scheme namely improved Kudryashov method for solving any nonlinear fractional differential model.Specifically,we apply the approach to the nonlinear space-time fractional model leading the wave to spread in electrical transmission lines(s-tfETL),the time fractional complex Schrödinger(tfcS),and the space-time M-fractional Schrödinger-Hirota(s-tM-fSH)models to verify the effectiveness of the proposed approach.The implementing of the introduced new technique based on the models provides us with periodic envelope,exponentially changeable soliton envelope,rational rogue wave,periodic rogue wave,combo periodic-soliton,and combo rational-soliton solutions,which are much interesting phenomena in nonlinear sciences.Thus the results disclose that the proposed technique is very effective and straight-forward,and such solutions of the models are much more fruitful than those from the generalized Kudryashov and the modified Kudryashov methods.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant Nos.62373197 and 61873326)。
文摘In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method.
文摘A new decentralized robust control method is discussed for a class of nonlinear interconnected largescale system with unknown bounded disturbance and unknown nonlinear function term. A decentralized control law is proposed which combines the approximation method of neural network with sliding mode control. The decentralized controller consists of an equivalent controller and an adaptive sliding mode controller. The sliding mode controller is a robust controller used to reduce the track error of the control system. The neural networks are used to approximate the unknown nonlinear functions, meanwhile the approximation errors of the neural networks are applied to the weight value updated law to improve performance of the system. Finally, an example demonstrates the availability of the decentralized control method.
基金Project supported by the National Natural Science Foundation of China (Grant No. 51175316)the Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20103108110006)
文摘We study the correlation between detrended fluctuation analysis（DFA） and the Lempel-Ziv complexity（LZC） in nonlinear time series analysis in this paper.Typical dynamic systems including a logistic map and a Duffing model are investigated.Moreover,the influence of Gaussian random noise on both the DFA and LZC are analyzed.The results show a high correlation between the DFA and LZC,which can quantify the non-stationarity and the nonlinearity of the time series,respectively.With the enhancement of the random component,the exponent α and the normalized complexity index C show increasing trends.In addition,C is found to be more sensitive to the fluctuation in the nonlinear time series than α.Finally,the correlation between the DFA and LZC is applied to the extraction of vibration signals for a reciprocating compressor gas valve,and an effective fault diagnosis result is obtained.
文摘The compact implicit integration factor （cIIF） method is an efficient time discretization scheme for stiff nonlinear diffusion equations in two and three spatial dimensions. In the current work, we apply the cIIF method to some complex-valued nonlinear evolutionary equations such as the nonlinear SchrSdinger （NLS） equation and the complex Ginzburg-Landau （GL） equation. Detailed algorithm formulation and practical implementation of cIIF method are performed. The numerical results indicate that this method is very accurate and efficient.
文摘This paper deals with a nonlinear boundary value problem for a complex equation W_z = H(Z,W,W_z),Z ∈G : |Z|<1 with boundary eondition of the form I.l-i Re[Z-W(Z)] = ψ(Z,W(Z)) + Re[λ_0+sum from k=1 to |n|-1(λ_k + iλ_k)Z^k],Z∈Γ:|z|=1 k--1 in which the index is negative. By establishing a priori estimate and using the imbdding method combined with the the Newton interation procedure, it is proved that the above problem is solvable and the solution is unique in C^l+a(g) ,O<a<].
基金supported by the National Natural Science Foundation of China(Nos.12172078,51576026)Fundamental Research Funds for the Central Universities in China(No.DUT21LK04)。
文摘Accurately solving transient nonlinear inverse heat conduction problems in complex structures is of great importance to provide key parameters for modeling coupled heat transfer process and the structure’s optimization design.The finite element method in ABAQUS is employed to solve the direct transient nonlinear heat conduction problem.Improved particle swarm optimization(PSO)method is developed and used to solve the transient nonlinear inverse problem.To investigate the inverse performances,some numerical tests are provided.Boundary conditions at inaccessible surfaces of a scramjet combustor with the regenerative cooling system are inversely identified.The results show that the new methodology can accurately and efficiently determine the boundary conditions in the scramjet combustor with the regenerative cooling system.By solving the transient nonlinear inverse problem,the improved particle swarm optimization for solving the transient nonlinear inverse heat conduction problem in a complex structure is verified.
基金Project supported by the Young Project of Hubei Provincial Department of Education,China(Grant No.Q20111309)the Key Program of Hubei Provincial Department of Education,China(Grant No.D20101304)
文摘We investigate the impulsive synchronization of a nonlinear coupled complex network with a delay node. Both delay coupling and non-delay coupling, as well as the symmetrical coupling matrix and the asymmetrical coupling matrix are considered. Based on the comparison theorem of an impulsive differential system, some novel synchronization criteria are derived. Finally, numerical simulations demonstrate the effectiveness of the proposed synchronization criteria.
文摘Cylindrical and spherical dust-electron-acoustic （DEA） shock waves and double layers in an unmagnetized, col- lisionless, complex or dusty plasma system are carried out. The plasma system is assumed to be composed of inertial and viscous cold electron fluids, nonextensive distributed hot electrons, Maxwellian ions, and negatively charged stationary dust grains. The standard reductive perturbation technique is used to derive the nonlinear dynamical equations, that is, the nonplanar Burgers equation and the nonplanar further Burgers equation. They are also numerically analyzed to investigate the basic features of shock waves and double layers （DLs）. It is observed that the roles of the viscous cold electron fluids, nonextensivity of hot electrons, and other plasma parameters in this investigation have significantly modified the basic features （such as, polarity, amplitude and width） of the nonplanar DEA shock waves and DLs. It is also observed that the strength of the shock is maximal for the spherical geometry, intermediate for cylindrical geometry, while it is minimal for the planar geometry. The findings of our results obtained from this theoretical investigation may be useful in understanding the nonlinear phenomena associated with the nonplanar DEA waves in both space and laboratory plasmas.
文摘Duality analysis of time series and complex networks has been a frontier topic during the last several decades.According to some recent approaches in this direction,the intrinsic dynamics of typical nonlinear systems can be better characterized by considering the related nonlinear time series from the perspective of networks science.In this paper,the associated network family of the unified piecewise-linear(PWL)chaotic family,which can bridge the gap of the PWL chaotic Lorenz system and the PWL chaotic Chen system,was firstly constructed and analyzed.We constructed the associated network family via the original and the modified frequency-degree mapping strategy,as well as the classical visibility graph and horizontal visibility graph strategy,after removing the transient states.Typical related network characteristics,including the network fractal dimension,of the associated network family,are computed with changes of single key parameter a.These characteristic vectors of the network are also compared with the largest Lyapunov exponent(LLE)vector of the related original dynamical system.It can be found that,some network characteristics are highly correlated with LLE vector of the original nonlinear system,i.e.,there is an internal consistency between the largest Lyapunov exponents,some typical associated network characteristics,and the related network fractal dimension index.Numerical results show that the modified frequency-degree mapping strategy can demonstrate highest correlation,which means it can behave better to capture the intrinsic characteristics of the unified PWL chaotic family.
基金Project supported by the National Natural Science Foundation of China (Grant Nos 50674070 and 60374041)the National High Technology Research and Development Program of China (Grant No 2007AA06Z231)
文摘Complex networks have established themselves in recent years as being particularly suitable and flexible for representing and modelling many complex natural and artificial systems. Oil-water two-phase flow is one of the most complex systems. In this paper, we use complex networks to study the inclined oil water two-phase flow. Two different complex network construction methods are proposed to build two types of networks, i.e. the flow pattern complex network （FPCN） and fluid dynamic complex network （FDCN）. Through detecting the community structure of FPCN by the community-detection algorithm based on K-means clustering, useful and interesting results are found which can be used for identifying three inclined oil-water flow patterns. To investigate the dynamic characteristics of the inclined oil-water two-phase flow, we construct 48 FDCNs under different flow conditions, and find that the power-law exponent and the network information entropy, which are sensitive to the flow pattern transition, can both characterize the nonlinear dynamics of the inclined oil-water two-phase flow. In this paper, from a new perspective, we not only introduce a complex network theory into the study of the oil-water two-phase flow but also indicate that the complex network may be a powerful tool for exploring nonlinear time series in practice.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.41775081,41975100,41901016,and 41875100)the Innovation Project of the China Meteorological Administration(Grant No.CXFZ2021Z034)the National Key Research and Development Program of China(Grant No.2018YFC1507702)。
文摘The uneven spatial distribution of stations providing precipitable water vapor(PWV)observations in China hinders the effective use of these data in assimilation,nowcasting,and prediction.In this study,we proposed a complex network framework for exploring the topological structure and the collective behavior of PWV in the mainland of China.We used the Pearson correlation coefficient and transfer entropy to measure the linear and nonlinear relationships of PWV amongst different stations and to set up the undirected and directed complex networks,respectively.Our findings revealed the statistical and geographical distribution of the variables influencing PWV networks and identified the vapor information source and sink stations.Specifically,the findings showed that the statistical and spatial distributions of the undirected and directed complex vapor networks in terms of degree and distance were similar to each other(the common interaction mode for vapor stations and their locations).The betweenness results displayed different features.The largest betweenness ratio for directed networks tended to be larger than that of the undirected networks,implying that the transfer of directed PWV networks was more efficient than that of the undirected networks.The findings of this study are heuristic and will be useful for constructing the best strategy for the PWV data in applications such as vapor observational networks design and precipitation prediction.
文摘We introduce a new integral scheme namely improved Kudryashov method for solving any nonlinear fractional differential model.Specifically,we apply the approach to the nonlinear space-time fractional model leading the wave to spread in electrical transmission lines(s-tfETL),the time fractional complex Schrödinger(tfcS),and the space-time M-fractional Schrödinger-Hirota(s-tM-fSH)models to verify the effectiveness of the proposed approach.The implementing of the introduced new technique based on the models provides us with periodic envelope,exponentially changeable soliton envelope,rational rogue wave,periodic rogue wave,combo periodic-soliton,and combo rational-soliton solutions,which are much interesting phenomena in nonlinear sciences.Thus the results disclose that the proposed technique is very effective and straight-forward,and such solutions of the models are much more fruitful than those from the generalized Kudryashov and the modified Kudryashov methods.
