The multiscale computational method with asymptotic analysis and reduced-order homogenization(ROH)gives a practical numerical solution for engineering problems,especially composite materials.Under the ROH framework,a ...The multiscale computational method with asymptotic analysis and reduced-order homogenization(ROH)gives a practical numerical solution for engineering problems,especially composite materials.Under the ROH framework,a partition-based unitcell structure at the mesoscale is utilized to give a mechanical state at the macro-scale quadrature point with pre-evaluated influence functions.In the past,the“1-phase,1-partition”rule was usually adopted in numerical analysis,where one constituent phase at the mesoscale formed one partition.The numerical cost then is significantly reduced by introducing an assumption that the mechanical responses are the same all the time at the same constituent,while it also introduces numerical inaccuracy.This study proposes a new partitioning method for fibrous unitcells under a reduced-order homogenization methodology.In this method,the fiber phase remains 1 partition,but the matrix phase is divided into 2 partitions,which refers to the“12”partitioning scheme.Analytical elastic influence+functions are derived by introducing the elastic strain energy equivalence(Hill-Mandel condition).This research also obtains the analytical eigenstrain influence functions by alleviating the so-called“inclusion-locking”phenomenon.In addition,a numerical approach to minimize the error of strain energy density is introduced to determine the partitioning of the matrix phase.Several numerical examples are presented to compare the differences among direct numerical simulation(DNS),“11”,and“12”partitioning schemes.The numerical simulations show improved++numerical accuracy by the“12”partitioning scheme.展开更多
With the intelligent transformation of process manufacturing,accurate and comprehensive perception information is fundamental for application of artificial intelligence methods.In zinc smelting,the fluidized bed roast...With the intelligent transformation of process manufacturing,accurate and comprehensive perception information is fundamental for application of artificial intelligence methods.In zinc smelting,the fluidized bed roaster is a key piece of large-scale equipment and plays a critical role in the manufacturing industry;its internal temperature field directly determines the quality of zinc calcine and other related products.However,due to its vast spatial dimensions,the limited observation methods,and the complex multiphase,multifield coupled reaction atmosphere inside it,accurately and timely perceiving its temperature field remains a significant challenge.To address these challenges,a spatial-temporal reduced-order model(STROM)is proposed,which can realize fast and accurate temperature field perception based on sparse observation data.Specifically,to address the difficulty in matching the initial physical field with the sparse observation data,an initial field construction based on data assimilation(IFCDA)method is proposed to ensure that the initial conditions of the model can be matched with the actual operation state,which provides a basis for constructing a high-precision computational fluid dynamics(CFD)model.Then,to address the high simulation cost of high-precision CFD models under full working conditions,a high uniformity(HU)-orthogonal test design(OTD)method with the centered L2 deviation is innovatively proposed to ensure high information coverage of the temperature field dataset under typical working conditions in terms of multiple factors and levels of the component,feed,and blast parameters.Finally,to address the difficulty in real-time and accurate temperature field prediction,considering the spatial correlation between the observed temperature and the temperature field,as well as the dynamic correlation of the observed temperature in the time dimension,a spatial-temporal predictive model(STPM)is established,which realizes rapid prediction of the temperature field through sparse observa-tion data.To verify the accuracy and validity of the proposed method,CFD model validation and reduced-order model prediction experiments are designed,and the results show that the proposed method can realize high-precision and fast prediction of the roaster temperature field under different working conditions through sparse observation data.Compared with the CFD model,the prediction root-mean-square error(RMSE)of STROM is less than 0.038,and the computational efficiency is improved by 3.4184×10^(4)times.In particular,STROM also has a good prediction ability for unmodeled conditions,with a prediction RMSE of less than 0.1089.展开更多
During the startup of the hydraulic turbine generators,the hybrid magnetic bearing support system exhibits displacement fluctuations,and the nonlinearity and strong coupling characteristics of the magnetic bearings li...During the startup of the hydraulic turbine generators,the hybrid magnetic bearing support system exhibits displacement fluctuations,and the nonlinearity and strong coupling characteristics of the magnetic bearings limit the accuracy of rotor modeling,making traditional control methods difficult to adapt to parameter variations.To suppress startup disturbances and achieve a control strategy with low computational complexity and high precision,this paper proposes a five-degree-of-freedom hybrid magnetic bearing control strategy based on an improved cascaded reduced-order linear active disturbance rejection controller(CRLADRC).The front-stage reduced-order linear extended state observer(FRLESO)reduces the system’s computational complexity,enabling the system to maintain stability during motor startup disturbances.The second-stage reduced-order linear extended state observer(SRLESO)further enhances the system’s disturbance estimation accuracy while maintaining low computational complexity.Furthermore,the disturbance rejection and noise suppression capabilities are analyzed in the frequency domain and the stability of the proposed control method is proven using Lyapunov theory.Experimental results indicate that the proposed strategy effectively reduces displacement fluctuations in the hybrid magnetic bearing support system during motor startup,significantly enhancing the system’s robustness.展开更多
A modified reduced-order method for RC networks which takes a division-and-conquest strategy is presented.The whole network is partitioned into a set of sub-networks at first,then each of them is reduced by Krylov sub...A modified reduced-order method for RC networks which takes a division-and-conquest strategy is presented.The whole network is partitioned into a set of sub-networks at first,then each of them is reduced by Krylov subspace techniques,and finally all the reduced sub-networks are incorporated together.With some accuracy,this method can reduce the number of both nodes and components of the circuit comparing to the traditional methods which usually only offer a reduced net with less nodes.This can markedly accelerate the sparse-matrix-based simulators whose performance is dominated by the entity of the matrix or the number of components of the circuits.展开更多
A Non-Intrusive Reduced-Order Model(NIROM)based on Proper Orthogonal Decomposition(POD)has been proposed for predicting the flow fields of transonic airfoils with geometry parameters.To provide a better reduced-order ...A Non-Intrusive Reduced-Order Model(NIROM)based on Proper Orthogonal Decomposition(POD)has been proposed for predicting the flow fields of transonic airfoils with geometry parameters.To provide a better reduced-order subspace to approximate the real flow field,a domain decomposition method has been used to separate the hard-to-predict regions from the full field and POD has been adopted in the regions individually.An Artificial Neural Network(ANN)has replaced the Radial Basis Function(RBF)to interpolate the coefficients of the POD modes,aiming at improving the approximation accuracy of the NIROM for non-samples.When predicting the flow fields of transonic airfoils,the proposed NIROM has demonstrated a high performance.展开更多
Recently, flutter active control using linear parameter varying（LPV） framework has attracted a lot of attention. LPV control synthesis usually generates controllers that are at least of the same order as the aeroela...Recently, flutter active control using linear parameter varying（LPV） framework has attracted a lot of attention. LPV control synthesis usually generates controllers that are at least of the same order as the aeroelastic models. Therefore, the reduced-order model is required by synthesis for avoidance of large computation cost and high-order controller. This paper proposes a new procedure for generation of accurate reduced-order linear time-invariant（LTI） models by using system identification from flutter testing data. The proposed approach is in two steps. The well-known poly-reference least squares complex frequency（p-LSCF） algorithm is firstly employed for modal parameter identification from frequency response measurement. After parameter identification,the dominant physical modes are determined by clear stabilization diagrams and clustering technique. In the second step, with prior knowledge of physical poles, the improved frequencydomain maximum likelihood（ML） estimator is presented for building accurate reduced-order model. Before ML estimation, an improved subspace identification considering the poles constraint is also proposed for initializing the iterative procedure. Finally, the performance of the proposed procedure is validated by real flight flutter test data.展开更多
A reduced-order extrapolation algorithm based on Crank-Nicolson least-squares mixed finite element （CNLSMFE） formulation and proper orthogonal decomposition （POD） technique for two-dimensional （2D） Sobolev equat...A reduced-order extrapolation algorithm based on Crank-Nicolson least-squares mixed finite element （CNLSMFE） formulation and proper orthogonal decomposition （POD） technique for two-dimensional （2D） Sobolev equations is established. The error estimates of the reduced-order CNLSMFE solutions and the implementation for the reduced-order extrapolation algorithm are provided. A numerical example is used to show that the results of numerical computations are consistent with theoretical conclusions. Moreover, it is shown that the reduced-order extrapolation algorithm is feasible and efficient for seeking numerical solutions to 2D Sobolev equations.展开更多
Formation control of discrete-time linear multi-agent systems using directed switching topology is considered in this work via a reduced-order observer, in which a formation control protocol is proposed under the assu...Formation control of discrete-time linear multi-agent systems using directed switching topology is considered in this work via a reduced-order observer, in which a formation control protocol is proposed under the assumption that each directed communication topology has a directed spanning tree. By utilizing the relative outputs of neighboring agents, a reduced-order observer is designed for each following agent. A multi-step control algorithm is established based on the Lyapunov method and the modified discrete-time algebraic Riccati equation. A sufficient condition is given to ensure that the discrete-time linear multi-agent system can achieve the expected leader-following formation.Finally, numerical examples are provided so as to demonstrate the effectiveness of the obtained results.展开更多
In networked robot manipulators that deeply integrate control, communication and computation, the controller design needs to take into consideration the limited or costly system resources and the presence of disturban...In networked robot manipulators that deeply integrate control, communication and computation, the controller design needs to take into consideration the limited or costly system resources and the presence of disturbances/uncertainties. To cope with these requirements, this paper proposes a novel dynamic event-triggered robust tracking control method for a onedegree of freedom(DOF) link manipulator with external disturbance and system uncertainties via a reduced-order generalized proportional-integral observer(GPIO). By only using the sampled-data position signal, a new sampled-data robust output feedback tracking controller is proposed based on a reduced-order GPIO to attenuate the undesirable influence of the external disturbance and the system uncertainties. To save the communication resources, we propose a discrete-time dynamic event-triggering mechanism(DETM), where the estimates and the control signal are transmitted and computed only when the proposed discrete-time DETM is violated. It is shown that with the proposed control method, both tracking control properties and communication properties can be significantly improved. Finally, simulation results are shown to demonstrate the feasibility and efficacy of the proposed control approach.展开更多
The reduced-order finite element method （FEM） based on a proper orthogo- nal decomposition （POD） theory is applied to the time fractional Tricomi-type equation. The present method is an improvement on the general ...The reduced-order finite element method （FEM） based on a proper orthogo- nal decomposition （POD） theory is applied to the time fractional Tricomi-type equation. The present method is an improvement on the general FEM. It can significantly save mem- ory space and effectively relieve the computing load due to its reconstruction of POD basis functions. Furthermore, the reduced-order finite element （FE） scheme is shown to be un- conditionally stable, and error estimation is derived in detail. Two numerical examples are presented to show the feasibility and effectiveness of the method for time fractional differential equations （FDEs）.展开更多
This paper aims at solving the state filtering problem for linear systems with state constraints. Three classes of typical state constraints, i.e., linear equality, quadratic equality and inequality, are discussed. By...This paper aims at solving the state filtering problem for linear systems with state constraints. Three classes of typical state constraints, i.e., linear equality, quadratic equality and inequality, are discussed. By using the linear relationships among different state variables, a reduced-order Kalman filter is derived for the system with linear equality constraints. Afterwards, such a solution is applied to the cases of the quadratic equality constraint and inequality constraints and the two constrained state filtering problems are transformed into two relative constrained optimization problems. Then they are solved by the Lagrangian multiplier and linear matrix inequality techniques, respectively. Finally, two simple tracking examples are provided to illustrate the effectiveness of the reduced-order filters.展开更多
With the rapid development of the world economy,IGBT has been widely used in motor drive and electric energy conversion.In order to timely detect the fatigue damage of IGBT,it is necessary to monitor the junction temp...With the rapid development of the world economy,IGBT has been widely used in motor drive and electric energy conversion.In order to timely detect the fatigue damage of IGBT,it is necessary to monitor the junction temperature of IGBT.In order to realize the fast calculation of IGBT junction temperature,a finite element method of IGBT temperature field reduction is proposed in this paper.Firstly,the finite element calculation process of IGBT temperature field is introduced and the linear equations of finite element calculation of temperature field are derived.Temperature field data of different working conditions are obtained by finite element simulation to form the sample space.Then the covariance matrix of the sample space is constructed,whose proper orthogonal decomposition and modal extraction are carried out.Reasonable basis vector space is selected to complete the low dimensional expression of temperature vector inside and outside the sample space.Finally,the reduced-order model of temperature field finite element is obtained and solved.The results of the reduced order model are compared with those of the finite element method,and the performance of the reduced-order model is evaluated from two aspects of accuracy and rapidity.展开更多
The projective reduced-order synchronization of two different chaotic systems with different orders is investigated based on the observer design in this paper.According to the observer theory,the reduced-order observe...The projective reduced-order synchronization of two different chaotic systems with different orders is investigated based on the observer design in this paper.According to the observer theory,the reduced-order observer is designed.The projective synchronization can be realized by choosing the transition matrix of the observer as a diagonal matrix.Further,the synchronization between hyperchaotic Chen system(fourth order)and Rssler system(third order)is taken as the example to demonstrate the effectiveness of the proposed observer.Numerical simulations confirm the effectiveness of the method.展开更多
The root multiple signal classification（root-MUSIC） algorithm is one of the most important techniques for direction of arrival（DOA） estimation. Using a uniform linear array（ULA） composed of M sensors, this metho...The root multiple signal classification（root-MUSIC） algorithm is one of the most important techniques for direction of arrival（DOA） estimation. Using a uniform linear array（ULA） composed of M sensors, this method usually estimates L signal DOAs by finding roots that lie closest to the unit circle of a（2M-1）-order polynomial, where L 〈 M. A novel efficient root-MUSIC-based method for direction estimation is presented, in which the order of polynomial is efficiently reduced to 2L. Compared with the unitary root-MUSIC（U-root-MUSIC） approach which involves real-valued computations only in the subspace decomposition stage, both tasks of subspace decomposition and polynomial rooting are implemented with real-valued computations in the new technique,which hence shows a significant efficiency advantage over most state-of-the-art techniques. Numerical simulations are conducted to verify the correctness and efficiency of the new estimator.展开更多
A new kind of generalized reduced-order synchronization of different chaotic systems is proposed in this paper. It is shown that dynamical evolution of third-order oscillator can be synchronized with the canonical pro...A new kind of generalized reduced-order synchronization of different chaotic systems is proposed in this paper. It is shown that dynamical evolution of third-order oscillator can be synchronized with the canonical projection of a fourth-order chaotic system generated through nonsingular states transformation from a cell neural net chaotic system. In this sense, it is said that generalized synchronization is achieved in reduced-order. The synchronization discussed here expands the scope of reduced-order synchronization studied in relevant literatures. In this way, we can achieve generalized reduced-order synchronization between many famous chaotic systems such as the second-order Drifting system and the third-order Lorenz system by designing a fast slide mode controller. Simulation results are provided to verify the operation of the designed synchronization.展开更多
This article proposes an innovative strategy to the problem of non-linear estimation of states for electrical machine systems. This method allows the estimation of variables that are difficult to access or that are si...This article proposes an innovative strategy to the problem of non-linear estimation of states for electrical machine systems. This method allows the estimation of variables that are difficult to access or that are simply impossible to measure. Thus, as compared with a full-order sliding mode observer, in order to reduce the execution time of the estimation, a reduced-order discrete-time Extended sliding mode observer is proposed for on-line estimation of rotor flux, speed and rotor resistance in an induction motor using a robust feedback linearization control. Simulations results on Matlab-Simulink environment for a 1.8 kW induction motor are presented to prove the effectiveness and high robustness of the proposed nonlinear control and observer against modeling uncertainty and measurement noise.展开更多
The objective of this paper is to propose a reduced-order observer for a class of Lipschitz nonlinear discrete-time systems.The conditions that guarantee the existence of this observer are presented in the form of lin...The objective of this paper is to propose a reduced-order observer for a class of Lipschitz nonlinear discrete-time systems.The conditions that guarantee the existence of this observer are presented in the form of linear matrix inequalities(LMIs). To handle the Lipschitz nonlinearities, the Lipschitz condition and the Young′s relation are adequately operated to add more degrees of freedom to the proposed LMI. Necessary and sufficient conditions for the existence of the unbiased reduced-order observer are given. An extension to H_∞ performance analysis is considered in order to deal with H_∞ asymptotic stability of the estimation error in the presence of disturbances that affect the state of the system. To highlight the effectiveness of the proposed design methodology, three numerical examples are considered. Then, high performances are shown through real time implementation using the ARDUINO MEGA 2560 device.展开更多
The flow field with a high order scheme is usually calculated so as to solve complex flow problems and describe the flow structure accurately. However, there are two problems, i.e., the reduced-order boundary is inevi...The flow field with a high order scheme is usually calculated so as to solve complex flow problems and describe the flow structure accurately. However, there are two problems, i.e., the reduced-order boundary is inevitable and the order of the scheme at the discontinuous shock wave contained in the flow field as the supersonic flow field is low. It is questionable whether the reduced-order boundary and the low-order scheme at the shock wave have an effect on the numerical solution and accuracy of the flow field inside. In this paper, according to the actual situation of the direct numerical simulation of the flow field, two model equations with the exact solutions are solved, which are steady and unsteady, respectively, to study the question with a high order scheme at the interior of the domain and the reduced-order method at the boundary and center of the domain. Comparing with the exact solutions, it is found that the effect of reduced-order exists and cannot be ignored. In addition, the other two model equations with the exact solutions, which are often used in fluid mechanics, are also studied with the same process for the reduced-order problem.展开更多
This paper is devoted to application of the Reduced-Order Model(ROM)based on Volterra series to prediction of lift and drag forces due to airfoil periodic translation in transonic flow region.When there is large ampli...This paper is devoted to application of the Reduced-Order Model(ROM)based on Volterra series to prediction of lift and drag forces due to airfoil periodic translation in transonic flow region.When there is large amplitude oscillation of the relative Mach number,as appeared in helicopter rotor movement in forward flight,the conventional Volterra ROM is found to be unsatisfactory.To cover such applications,a matched Volterra ROM,inspired from previous multistep nonlinear indicial response method based on Duhamel integration,is thus considered,in which the step motions are defined inside a number of equal intervals with both positive and negative step motions to match the airfoil forward and backward movement,and the kernel functions are constructed independently at each interval.It shows that,at least for the translation movement considered,this matched Volterra ROM greatly improves the accuracy of prediction.Moreover,the matched Volterra ROM,with the total number of step motions and thus the computational cost close to those of the conventional Volterra ROM method,has the additional advantage that the same set of kernels can match various translation motions with different starting conditions so the kernels can be predesigned without knowing the specific motion of airfoil.展开更多
An improved Reduced-Order Model(ROM)is proposed based on a flow-solution preprocessing operation and a fast sampling strategy to efficiently and accurately predict ionized hypersonic flows.This ROM is generated in low...An improved Reduced-Order Model(ROM)is proposed based on a flow-solution preprocessing operation and a fast sampling strategy to efficiently and accurately predict ionized hypersonic flows.This ROM is generated in low-dimensional space by performing the Proper Orthogonal Decomposition(POD)on snapshots and is coupled with the Radial Basis Function(RBF)to achieve fast prediction speed.However,due to the disparate scales in the ionized flow field,the conventional ROM usually generates spurious negative errors.Here,this issue is addressed by performing flow-solution preprocessing in logarithmic space to improve the conventional ROM.Then,extra orthogonal polynomials are introduced in the RBF interpolation to achieve additional improvement of the prediction accuracy.In addition,to construct high-efficiency snapshots,a trajectory-constrained adaptive sampling strategy based on convex hull optimization is developed.To evaluate the performance of the proposed fast prediction method,two hypersonic vehicles with classic configurations,i.e.a wave-rider and a reentry capsule,are used to validate the proposed method.Both two cases show that the proposed fast prediction method has high accuracy near the vehicle surface and the free-stream region where the flow field is smooth.Compared with the conventional ROM prediction,the prediction results are significantly improved by the proposed method around the discontinuities,e.g.the shock wave and the ionized layer.As a result,the proposed fast prediction method reduces the error of the conventional ROM by at least 45%,with a speedup of approximately 2.0×105compared to the Computational Fluid Dynamic(CFD)simulations.These test cases demonstrate that the method developed here is efficient and accurate for predicting ionized hypersonic flows.展开更多
基金funded by the National Key R&D Program of China(Grant No.2023YFA1008901)the National Natural Science Foundation of China(Grant Nos.11988102,12172009)“The Fundamental Research Funds for the Central Universities,Peking University”.
文摘The multiscale computational method with asymptotic analysis and reduced-order homogenization(ROH)gives a practical numerical solution for engineering problems,especially composite materials.Under the ROH framework,a partition-based unitcell structure at the mesoscale is utilized to give a mechanical state at the macro-scale quadrature point with pre-evaluated influence functions.In the past,the“1-phase,1-partition”rule was usually adopted in numerical analysis,where one constituent phase at the mesoscale formed one partition.The numerical cost then is significantly reduced by introducing an assumption that the mechanical responses are the same all the time at the same constituent,while it also introduces numerical inaccuracy.This study proposes a new partitioning method for fibrous unitcells under a reduced-order homogenization methodology.In this method,the fiber phase remains 1 partition,but the matrix phase is divided into 2 partitions,which refers to the“12”partitioning scheme.Analytical elastic influence+functions are derived by introducing the elastic strain energy equivalence(Hill-Mandel condition).This research also obtains the analytical eigenstrain influence functions by alleviating the so-called“inclusion-locking”phenomenon.In addition,a numerical approach to minimize the error of strain energy density is introduced to determine the partitioning of the matrix phase.Several numerical examples are presented to compare the differences among direct numerical simulation(DNS),“11”,and“12”partitioning schemes.The numerical simulations show improved++numerical accuracy by the“12”partitioning scheme.
基金supported in part by the National Key Research and Development Program of China(2022YFB3304900)in part by the National Natural Science Foundation of China(62394340 and 62073340)in part by the Science and Technology Innovation Program of Hunan Province(2022JJ10083).
文摘With the intelligent transformation of process manufacturing,accurate and comprehensive perception information is fundamental for application of artificial intelligence methods.In zinc smelting,the fluidized bed roaster is a key piece of large-scale equipment and plays a critical role in the manufacturing industry;its internal temperature field directly determines the quality of zinc calcine and other related products.However,due to its vast spatial dimensions,the limited observation methods,and the complex multiphase,multifield coupled reaction atmosphere inside it,accurately and timely perceiving its temperature field remains a significant challenge.To address these challenges,a spatial-temporal reduced-order model(STROM)is proposed,which can realize fast and accurate temperature field perception based on sparse observation data.Specifically,to address the difficulty in matching the initial physical field with the sparse observation data,an initial field construction based on data assimilation(IFCDA)method is proposed to ensure that the initial conditions of the model can be matched with the actual operation state,which provides a basis for constructing a high-precision computational fluid dynamics(CFD)model.Then,to address the high simulation cost of high-precision CFD models under full working conditions,a high uniformity(HU)-orthogonal test design(OTD)method with the centered L2 deviation is innovatively proposed to ensure high information coverage of the temperature field dataset under typical working conditions in terms of multiple factors and levels of the component,feed,and blast parameters.Finally,to address the difficulty in real-time and accurate temperature field prediction,considering the spatial correlation between the observed temperature and the temperature field,as well as the dynamic correlation of the observed temperature in the time dimension,a spatial-temporal predictive model(STPM)is established,which realizes rapid prediction of the temperature field through sparse observa-tion data.To verify the accuracy and validity of the proposed method,CFD model validation and reduced-order model prediction experiments are designed,and the results show that the proposed method can realize high-precision and fast prediction of the roaster temperature field under different working conditions through sparse observation data.Compared with the CFD model,the prediction root-mean-square error(RMSE)of STROM is less than 0.038,and the computational efficiency is improved by 3.4184×10^(4)times.In particular,STROM also has a good prediction ability for unmodeled conditions,with a prediction RMSE of less than 0.1089.
基金supported by the National Natural Science Foundation of China under Grant 52302458the CAS Project for Young Scientists in Basic Research,Grant No.YSBR-045.
文摘During the startup of the hydraulic turbine generators,the hybrid magnetic bearing support system exhibits displacement fluctuations,and the nonlinearity and strong coupling characteristics of the magnetic bearings limit the accuracy of rotor modeling,making traditional control methods difficult to adapt to parameter variations.To suppress startup disturbances and achieve a control strategy with low computational complexity and high precision,this paper proposes a five-degree-of-freedom hybrid magnetic bearing control strategy based on an improved cascaded reduced-order linear active disturbance rejection controller(CRLADRC).The front-stage reduced-order linear extended state observer(FRLESO)reduces the system’s computational complexity,enabling the system to maintain stability during motor startup disturbances.The second-stage reduced-order linear extended state observer(SRLESO)further enhances the system’s disturbance estimation accuracy while maintaining low computational complexity.Furthermore,the disturbance rejection and noise suppression capabilities are analyzed in the frequency domain and the stability of the proposed control method is proven using Lyapunov theory.Experimental results indicate that the proposed strategy effectively reduces displacement fluctuations in the hybrid magnetic bearing support system during motor startup,significantly enhancing the system’s robustness.
文摘A modified reduced-order method for RC networks which takes a division-and-conquest strategy is presented.The whole network is partitioned into a set of sub-networks at first,then each of them is reduced by Krylov subspace techniques,and finally all the reduced sub-networks are incorporated together.With some accuracy,this method can reduce the number of both nodes and components of the circuit comparing to the traditional methods which usually only offer a reduced net with less nodes.This can markedly accelerate the sparse-matrix-based simulators whose performance is dominated by the entity of the matrix or the number of components of the circuits.
基金supported by the National Natural Science Foundation of China(No.11802245).
文摘A Non-Intrusive Reduced-Order Model(NIROM)based on Proper Orthogonal Decomposition(POD)has been proposed for predicting the flow fields of transonic airfoils with geometry parameters.To provide a better reduced-order subspace to approximate the real flow field,a domain decomposition method has been used to separate the hard-to-predict regions from the full field and POD has been adopted in the regions individually.An Artificial Neural Network(ANN)has replaced the Radial Basis Function(RBF)to interpolate the coefficients of the POD modes,aiming at improving the approximation accuracy of the NIROM for non-samples.When predicting the flow fields of transonic airfoils,the proposed NIROM has demonstrated a high performance.
基金co-supported by the National Natural Science Foundation of China (Nos. 61134004 and 61573289)Aeronautical Science Foundation of China (No. 20140753010)the Fundamental Research Funds for the Central Universities (No. 3102015BJ004)
文摘Recently, flutter active control using linear parameter varying（LPV） framework has attracted a lot of attention. LPV control synthesis usually generates controllers that are at least of the same order as the aeroelastic models. Therefore, the reduced-order model is required by synthesis for avoidance of large computation cost and high-order controller. This paper proposes a new procedure for generation of accurate reduced-order linear time-invariant（LTI） models by using system identification from flutter testing data. The proposed approach is in two steps. The well-known poly-reference least squares complex frequency（p-LSCF） algorithm is firstly employed for modal parameter identification from frequency response measurement. After parameter identification,the dominant physical modes are determined by clear stabilization diagrams and clustering technique. In the second step, with prior knowledge of physical poles, the improved frequencydomain maximum likelihood（ML） estimator is presented for building accurate reduced-order model. Before ML estimation, an improved subspace identification considering the poles constraint is also proposed for initializing the iterative procedure. Finally, the performance of the proposed procedure is validated by real flight flutter test data.
基金Supported by the National Natural Science Foundation of China(11271127)Science Research Projectof Guizhou Province Education Department(QJHKYZ[2013]207)
文摘A reduced-order extrapolation algorithm based on Crank-Nicolson least-squares mixed finite element （CNLSMFE） formulation and proper orthogonal decomposition （POD） technique for two-dimensional （2D） Sobolev equations is established. The error estimates of the reduced-order CNLSMFE solutions and the implementation for the reduced-order extrapolation algorithm are provided. A numerical example is used to show that the results of numerical computations are consistent with theoretical conclusions. Moreover, it is shown that the reduced-order extrapolation algorithm is feasible and efficient for seeking numerical solutions to 2D Sobolev equations.
基金supported by National Natural Science Foundation of China(61573200,61973175)the Fundamental Research Funds for the Central Universities,Nankai University(63201196)。
文摘Formation control of discrete-time linear multi-agent systems using directed switching topology is considered in this work via a reduced-order observer, in which a formation control protocol is proposed under the assumption that each directed communication topology has a directed spanning tree. By utilizing the relative outputs of neighboring agents, a reduced-order observer is designed for each following agent. A multi-step control algorithm is established based on the Lyapunov method and the modified discrete-time algebraic Riccati equation. A sufficient condition is given to ensure that the discrete-time linear multi-agent system can achieve the expected leader-following formation.Finally, numerical examples are provided so as to demonstrate the effectiveness of the obtained results.
基金supported in part by the National Natural Science Foundation of China(61473080,61573099,61973080,61750110525,61633003)。
文摘In networked robot manipulators that deeply integrate control, communication and computation, the controller design needs to take into consideration the limited or costly system resources and the presence of disturbances/uncertainties. To cope with these requirements, this paper proposes a novel dynamic event-triggered robust tracking control method for a onedegree of freedom(DOF) link manipulator with external disturbance and system uncertainties via a reduced-order generalized proportional-integral observer(GPIO). By only using the sampled-data position signal, a new sampled-data robust output feedback tracking controller is proposed based on a reduced-order GPIO to attenuate the undesirable influence of the external disturbance and the system uncertainties. To save the communication resources, we propose a discrete-time dynamic event-triggering mechanism(DETM), where the estimates and the control signal are transmitted and computed only when the proposed discrete-time DETM is violated. It is shown that with the proposed control method, both tracking control properties and communication properties can be significantly improved. Finally, simulation results are shown to demonstrate the feasibility and efficacy of the proposed control approach.
基金Project supported by the National Natural Science Foundation of China(Nos.11361035 and 11301258)the Natural Science Foundation of Inner Mongolia(Nos.2012MS0106 and 2012MS0108)
文摘The reduced-order finite element method （FEM） based on a proper orthogo- nal decomposition （POD） theory is applied to the time fractional Tricomi-type equation. The present method is an improvement on the general FEM. It can significantly save mem- ory space and effectively relieve the computing load due to its reconstruction of POD basis functions. Furthermore, the reduced-order finite element （FE） scheme is shown to be un- conditionally stable, and error estimation is derived in detail. Two numerical examples are presented to show the feasibility and effectiveness of the method for time fractional differential equations （FDEs）.
基金supported by the National Key Basic Research Development Project (973 Program) (2012CB821205)the Natural Scientific Research Innovation Foundation in Harbin Institute of Technology(HIT.NSRIF.2009004)
文摘This paper aims at solving the state filtering problem for linear systems with state constraints. Three classes of typical state constraints, i.e., linear equality, quadratic equality and inequality, are discussed. By using the linear relationships among different state variables, a reduced-order Kalman filter is derived for the system with linear equality constraints. Afterwards, such a solution is applied to the cases of the quadratic equality constraint and inequality constraints and the two constrained state filtering problems are transformed into two relative constrained optimization problems. Then they are solved by the Lagrangian multiplier and linear matrix inequality techniques, respectively. Finally, two simple tracking examples are provided to illustrate the effectiveness of the reduced-order filters.
基金supported in part by Heilongjiang Provincial Natural Science Foundation of China under Project TD2021E004in part by Ningbo Science and Technology Bureau under S&T Innovation 2025 Major Special Programme with project code 2019B10071。
文摘With the rapid development of the world economy,IGBT has been widely used in motor drive and electric energy conversion.In order to timely detect the fatigue damage of IGBT,it is necessary to monitor the junction temperature of IGBT.In order to realize the fast calculation of IGBT junction temperature,a finite element method of IGBT temperature field reduction is proposed in this paper.Firstly,the finite element calculation process of IGBT temperature field is introduced and the linear equations of finite element calculation of temperature field are derived.Temperature field data of different working conditions are obtained by finite element simulation to form the sample space.Then the covariance matrix of the sample space is constructed,whose proper orthogonal decomposition and modal extraction are carried out.Reasonable basis vector space is selected to complete the low dimensional expression of temperature vector inside and outside the sample space.Finally,the reduced-order model of temperature field finite element is obtained and solved.The results of the reduced order model are compared with those of the finite element method,and the performance of the reduced-order model is evaluated from two aspects of accuracy and rapidity.
基金Sponsored by the National Natural Science Foundation of China(Grant No.50877007)the Fundamental Research Funds for the Central Universities(Grant No.DUT10LK12)
文摘The projective reduced-order synchronization of two different chaotic systems with different orders is investigated based on the observer design in this paper.According to the observer theory,the reduced-order observer is designed.The projective synchronization can be realized by choosing the transition matrix of the observer as a diagonal matrix.Further,the synchronization between hyperchaotic Chen system(fourth order)and Rssler system(third order)is taken as the example to demonstrate the effectiveness of the proposed observer.Numerical simulations confirm the effectiveness of the method.
基金supported by the National Natural Science Foundation of China(61501142)the Shandong Provincial Natural Science Foundation(ZR2014FQ003)+1 种基金the Special Foundation of China Postdoctoral Science(2016T90289)the China Postdoctoral Science Foundation(2015M571414)
文摘The root multiple signal classification（root-MUSIC） algorithm is one of the most important techniques for direction of arrival（DOA） estimation. Using a uniform linear array（ULA） composed of M sensors, this method usually estimates L signal DOAs by finding roots that lie closest to the unit circle of a（2M-1）-order polynomial, where L 〈 M. A novel efficient root-MUSIC-based method for direction estimation is presented, in which the order of polynomial is efficiently reduced to 2L. Compared with the unitary root-MUSIC（U-root-MUSIC） approach which involves real-valued computations only in the subspace decomposition stage, both tasks of subspace decomposition and polynomial rooting are implemented with real-valued computations in the new technique,which hence shows a significant efficiency advantage over most state-of-the-art techniques. Numerical simulations are conducted to verify the correctness and efficiency of the new estimator.
基金Project supported by the National Natural Science Foundation of China （Grant No 60374037） and the National High Technology Development Program of China （Grant No 2004BA204B08-02）.
文摘A new kind of generalized reduced-order synchronization of different chaotic systems is proposed in this paper. It is shown that dynamical evolution of third-order oscillator can be synchronized with the canonical projection of a fourth-order chaotic system generated through nonsingular states transformation from a cell neural net chaotic system. In this sense, it is said that generalized synchronization is achieved in reduced-order. The synchronization discussed here expands the scope of reduced-order synchronization studied in relevant literatures. In this way, we can achieve generalized reduced-order synchronization between many famous chaotic systems such as the second-order Drifting system and the third-order Lorenz system by designing a fast slide mode controller. Simulation results are provided to verify the operation of the designed synchronization.
文摘This article proposes an innovative strategy to the problem of non-linear estimation of states for electrical machine systems. This method allows the estimation of variables that are difficult to access or that are simply impossible to measure. Thus, as compared with a full-order sliding mode observer, in order to reduce the execution time of the estimation, a reduced-order discrete-time Extended sliding mode observer is proposed for on-line estimation of rotor flux, speed and rotor resistance in an induction motor using a robust feedback linearization control. Simulations results on Matlab-Simulink environment for a 1.8 kW induction motor are presented to prove the effectiveness and high robustness of the proposed nonlinear control and observer against modeling uncertainty and measurement noise.
文摘The objective of this paper is to propose a reduced-order observer for a class of Lipschitz nonlinear discrete-time systems.The conditions that guarantee the existence of this observer are presented in the form of linear matrix inequalities(LMIs). To handle the Lipschitz nonlinearities, the Lipschitz condition and the Young′s relation are adequately operated to add more degrees of freedom to the proposed LMI. Necessary and sufficient conditions for the existence of the unbiased reduced-order observer are given. An extension to H_∞ performance analysis is considered in order to deal with H_∞ asymptotic stability of the estimation error in the presence of disturbances that affect the state of the system. To highlight the effectiveness of the proposed design methodology, three numerical examples are considered. Then, high performances are shown through real time implementation using the ARDUINO MEGA 2560 device.
基金Project supported by the National Key Research and Development Project of China(No.2016YFA0401200)the National Natural Science Foundation of China(Nos.11672205 and11332007)
文摘The flow field with a high order scheme is usually calculated so as to solve complex flow problems and describe the flow structure accurately. However, there are two problems, i.e., the reduced-order boundary is inevitable and the order of the scheme at the discontinuous shock wave contained in the flow field as the supersonic flow field is low. It is questionable whether the reduced-order boundary and the low-order scheme at the shock wave have an effect on the numerical solution and accuracy of the flow field inside. In this paper, according to the actual situation of the direct numerical simulation of the flow field, two model equations with the exact solutions are solved, which are steady and unsteady, respectively, to study the question with a high order scheme at the interior of the domain and the reduced-order method at the boundary and center of the domain. Comparing with the exact solutions, it is found that the effect of reduced-order exists and cannot be ignored. In addition, the other two model equations with the exact solutions, which are often used in fluid mechanics, are also studied with the same process for the reduced-order problem.
文摘This paper is devoted to application of the Reduced-Order Model(ROM)based on Volterra series to prediction of lift and drag forces due to airfoil periodic translation in transonic flow region.When there is large amplitude oscillation of the relative Mach number,as appeared in helicopter rotor movement in forward flight,the conventional Volterra ROM is found to be unsatisfactory.To cover such applications,a matched Volterra ROM,inspired from previous multistep nonlinear indicial response method based on Duhamel integration,is thus considered,in which the step motions are defined inside a number of equal intervals with both positive and negative step motions to match the airfoil forward and backward movement,and the kernel functions are constructed independently at each interval.It shows that,at least for the translation movement considered,this matched Volterra ROM greatly improves the accuracy of prediction.Moreover,the matched Volterra ROM,with the total number of step motions and thus the computational cost close to those of the conventional Volterra ROM method,has the additional advantage that the same set of kernels can match various translation motions with different starting conditions so the kernels can be predesigned without knowing the specific motion of airfoil.
基金supported by the National Natural Science Foundation of China(Nos.11902271 and 91952203)the Fundamental Research Funds for the Central Universities of China(No.G2019KY05102)111 project on“Aircraft Complex Flows and the Control”of China(No.B17037)。
文摘An improved Reduced-Order Model(ROM)is proposed based on a flow-solution preprocessing operation and a fast sampling strategy to efficiently and accurately predict ionized hypersonic flows.This ROM is generated in low-dimensional space by performing the Proper Orthogonal Decomposition(POD)on snapshots and is coupled with the Radial Basis Function(RBF)to achieve fast prediction speed.However,due to the disparate scales in the ionized flow field,the conventional ROM usually generates spurious negative errors.Here,this issue is addressed by performing flow-solution preprocessing in logarithmic space to improve the conventional ROM.Then,extra orthogonal polynomials are introduced in the RBF interpolation to achieve additional improvement of the prediction accuracy.In addition,to construct high-efficiency snapshots,a trajectory-constrained adaptive sampling strategy based on convex hull optimization is developed.To evaluate the performance of the proposed fast prediction method,two hypersonic vehicles with classic configurations,i.e.a wave-rider and a reentry capsule,are used to validate the proposed method.Both two cases show that the proposed fast prediction method has high accuracy near the vehicle surface and the free-stream region where the flow field is smooth.Compared with the conventional ROM prediction,the prediction results are significantly improved by the proposed method around the discontinuities,e.g.the shock wave and the ionized layer.As a result,the proposed fast prediction method reduces the error of the conventional ROM by at least 45%,with a speedup of approximately 2.0×105compared to the Computational Fluid Dynamic(CFD)simulations.These test cases demonstrate that the method developed here is efficient and accurate for predicting ionized hypersonic flows.
