Virtual coupling is a novel technology that enables trains to run closely together without physical connections through communication and automation systems.The paper addresses an adaptive polynomial approximation alg...Virtual coupling is a novel technology that enables trains to run closely together without physical connections through communication and automation systems.The paper addresses an adaptive polynomial approximation algorithm for the cooperative control of high-speed trains(HSTs)under virtual coupling.It aims to solve the cooperative tracking control problem of HST formation operations under various scenarios,including known and unknown parameters.To enable the HST formation system to achieve cooperative operation while ensuring an appropriate spacing distance,the tracking errors of displacement and speed throughout the entire operation converge to zero.The proposed control strategy focuses on adopting polynomial approximation to handle unknown parameters,which are estimated via adaptive laws.Additionally,the unknown parameters of the HSTs are estimated online through adaptive laws.Experimental results verify the effectiveness of this method.展开更多
Fault isolation in dynamical systems is a challenging task due to modeling uncertainty and measurement noise,interactive effects of multiple faults and fault propagation.This paper proposes a unified approach for isol...Fault isolation in dynamical systems is a challenging task due to modeling uncertainty and measurement noise,interactive effects of multiple faults and fault propagation.This paper proposes a unified approach for isolation of multiple actuator or sensor faults in a class of nonlinear uncertain dynamical systems.Actuator and sensor fault isolation are accomplished in two independent modules,that monitor the system and are able to isolate the potential faulty actuator(s)or sensor(s).For the sensor fault isolation(SFI)case,a module is designed which monitors the system and utilizes an adaptive isolation threshold on the output residuals computed via a nonlinear estimation scheme that allows the isolation of single/multiple faulty sensor(s).For the actuator fault isolation(AFI)case,a second module is designed,which utilizes a learning-based scheme for adaptive approximation of faulty actuator(s)and,based on a reasoning decision logic and suitably designed AFI thresholds,the faulty actuator(s)set can be determined.The effectiveness of the proposed fault isolation approach developed in this paper is demonstrated through a simulation example.展开更多
Solving complex problems by multi-agent systems in distributed environments requires new approximate reasoning methods based on new computing paradigms. One such recently emerging computing paradigm is Granular Comput...Solving complex problems by multi-agent systems in distributed environments requires new approximate reasoning methods based on new computing paradigms. One such recently emerging computing paradigm is Granular Computing(GC). We discuss the Rough-Granular Computing(RGC) approach to modeling of computations in complex adaptive systems and multiagent systems as well as for approximate reasoning about the behavior of such systems. The RGC methods have been successfully applied for solving complex problems in areas such as identification of objects or behavioral patterns by autonomous systems, web mining, and sensor fusion.展开更多
The multilevel characteristic basis function method(MLCBFM)with the adaptive cross approximation(ACA)algorithm for accelerated solution of electrically large scattering problems is studied in this paper.In the convent...The multilevel characteristic basis function method(MLCBFM)with the adaptive cross approximation(ACA)algorithm for accelerated solution of electrically large scattering problems is studied in this paper.In the conventional MLCBFM based on Foldy-Lax multiple scattering equations,the improvement is only made in the generation of characteristic basis functions(CBFs).However,it does not provide a change in impedance matrix filling and reducing matrix calculation procedure,which is time-consuming.In reality,all the impedance and reduced matrix of each level of the MLCBFM have low-rank property and can be calculated efficiently.Therefore,ACA is used for the efficient generation of two-level CBFs and the fast calculation of reduced matrix in this study.Numerical results are given to demonstrate the accuracy and efficiency of the method.展开更多
Purpose–The quad-rotor is an under-actuation,strong coupled nonlinear system with parameters uncertainty,unmodeled disturbance and drive capability boundedness.The purpose of the paper is to design a flight control s...Purpose–The quad-rotor is an under-actuation,strong coupled nonlinear system with parameters uncertainty,unmodeled disturbance and drive capability boundedness.The purpose of the paper is to design a flight control system to regulate the aircraft track the desired trajectory and keep the attitude angles stable on account of these issues.Design/methodology/approach–Considering the dynamics of a quad-rotor,the closed-loop flight control system is divided into two nested loops:the translational outer-loop and the attitude inner-loop.In the outer-loop,the translational controller,which exports the desired attitude angles to the inner-loop,is designed based on bounded control technique.In consideration of the influence of uncertain rotational inertia and external disturbance,the backstepping sliding mode approach with adaptive gains is used in the inner-loop.The switching control strategy based on the sign functions of sliding surface is introduced into the design procedure with respect to the input saturation.Findings–The validity of the proposed flight control system was verified through numerical simulation and prototype flight experiment in this paper.Furthermore,with relation to the flying,the motor speed is kept in the predetermined scope.Originality/value–This article introduces a new flight control system designed for a quad-rotor.展开更多
In this work,we propose an adaptive learning approach based on temporal normalizing flows for solving time-dependent Fokker-Planck(TFP)equations.It is well known that solutions of such equations are probability densit...In this work,we propose an adaptive learning approach based on temporal normalizing flows for solving time-dependent Fokker-Planck(TFP)equations.It is well known that solutions of such equations are probability density functions,and thus our approach relies on modelling the target solutions with the temporal normalizing flows.The temporal normalizing flow is then trained based on the TFP loss function,without requiring any labeled data.Being a machine learning scheme,the proposed approach is mesh-free and can be easily applied to high dimensional problems.We present a variety of test problems to show the effectiveness of the learning approach.展开更多
Trefftz-finite element method(Trefftz-FEM),adaptive cross approximation BEM(ACA BEM)and continuous source function method(CSFM)are used for the simulation of composites reinforced by short fibers(CRSF)with the aim of ...Trefftz-finite element method(Trefftz-FEM),adaptive cross approximation BEM(ACA BEM)and continuous source function method(CSFM)are used for the simulation of composites reinforced by short fibers(CRSF)with the aim of showing the possibilities of reducing the problem of complicated and important interactions in such composite materials.展开更多
基金supported in part by the National Natural Science Foundation of China(Grant Nos.62203246 and 62003127)Shandong Provincial Natural Science Foundation(Grant No.ZR2024QF041)the Natural Science Foundation of Hebei Province(Grant No.F2023202060)。
文摘Virtual coupling is a novel technology that enables trains to run closely together without physical connections through communication and automation systems.The paper addresses an adaptive polynomial approximation algorithm for the cooperative control of high-speed trains(HSTs)under virtual coupling.It aims to solve the cooperative tracking control problem of HST formation operations under various scenarios,including known and unknown parameters.To enable the HST formation system to achieve cooperative operation while ensuring an appropriate spacing distance,the tracking errors of displacement and speed throughout the entire operation converge to zero.The proposed control strategy focuses on adopting polynomial approximation to handle unknown parameters,which are estimated via adaptive laws.Additionally,the unknown parameters of the HSTs are estimated online through adaptive laws.Experimental results verify the effectiveness of this method.
基金the European Research Council(ERC)under the ERC Synergy grant agreement No.951424(Water-Futures)the European Union’s Horizon 2020 research and innovation programme under grant agreement No.739551(KIOS CoE)the Government of the Republic of Cyprus through the Directorate General for European Programmes,Coordination and Development。
文摘Fault isolation in dynamical systems is a challenging task due to modeling uncertainty and measurement noise,interactive effects of multiple faults and fault propagation.This paper proposes a unified approach for isolation of multiple actuator or sensor faults in a class of nonlinear uncertain dynamical systems.Actuator and sensor fault isolation are accomplished in two independent modules,that monitor the system and are able to isolate the potential faulty actuator(s)or sensor(s).For the sensor fault isolation(SFI)case,a module is designed which monitors the system and utilizes an adaptive isolation threshold on the output residuals computed via a nonlinear estimation scheme that allows the isolation of single/multiple faulty sensor(s).For the actuator fault isolation(AFI)case,a second module is designed,which utilizes a learning-based scheme for adaptive approximation of faulty actuator(s)and,based on a reasoning decision logic and suitably designed AFI thresholds,the faulty actuator(s)set can be determined.The effectiveness of the proposed fault isolation approach developed in this paper is demonstrated through a simulation example.
基金The grant3 T11C 00226 from Min istroyf ScientifiRcesearchand InformationTechnologyoftheRepublicofPoland.
文摘Solving complex problems by multi-agent systems in distributed environments requires new approximate reasoning methods based on new computing paradigms. One such recently emerging computing paradigm is Granular Computing(GC). We discuss the Rough-Granular Computing(RGC) approach to modeling of computations in complex adaptive systems and multiagent systems as well as for approximate reasoning about the behavior of such systems. The RGC methods have been successfully applied for solving complex problems in areas such as identification of objects or behavioral patterns by autonomous systems, web mining, and sensor fusion.
基金supported by the National Natural Science Foundation of China (No.61401003)the Specialized Research Fund for the Doctoral Program of Higher Education of China (No.20123401110006)the Natural Science Research Project of Anhui Education ( No. KJ2015A436)
文摘The multilevel characteristic basis function method(MLCBFM)with the adaptive cross approximation(ACA)algorithm for accelerated solution of electrically large scattering problems is studied in this paper.In the conventional MLCBFM based on Foldy-Lax multiple scattering equations,the improvement is only made in the generation of characteristic basis functions(CBFs).However,it does not provide a change in impedance matrix filling and reducing matrix calculation procedure,which is time-consuming.In reality,all the impedance and reduced matrix of each level of the MLCBFM have low-rank property and can be calculated efficiently.Therefore,ACA is used for the efficient generation of two-level CBFs and the fast calculation of reduced matrix in this study.Numerical results are given to demonstrate the accuracy and efficiency of the method.
文摘Purpose–The quad-rotor is an under-actuation,strong coupled nonlinear system with parameters uncertainty,unmodeled disturbance and drive capability boundedness.The purpose of the paper is to design a flight control system to regulate the aircraft track the desired trajectory and keep the attitude angles stable on account of these issues.Design/methodology/approach–Considering the dynamics of a quad-rotor,the closed-loop flight control system is divided into two nested loops:the translational outer-loop and the attitude inner-loop.In the outer-loop,the translational controller,which exports the desired attitude angles to the inner-loop,is designed based on bounded control technique.In consideration of the influence of uncertain rotational inertia and external disturbance,the backstepping sliding mode approach with adaptive gains is used in the inner-loop.The switching control strategy based on the sign functions of sliding surface is introduced into the design procedure with respect to the input saturation.Findings–The validity of the proposed flight control system was verified through numerical simulation and prototype flight experiment in this paper.Furthermore,with relation to the flying,the motor speed is kept in the predetermined scope.Originality/value–This article introduces a new flight control system designed for a quad-rotor.
基金supported by the NSF of China(under grant numbers 12288201 and 11731006)the National Key R&D Program of China(2020YFA0712000)the Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDA25010404).
文摘In this work,we propose an adaptive learning approach based on temporal normalizing flows for solving time-dependent Fokker-Planck(TFP)equations.It is well known that solutions of such equations are probability density functions,and thus our approach relies on modelling the target solutions with the temporal normalizing flows.The temporal normalizing flow is then trained based on the TFP loss function,without requiring any labeled data.Being a machine learning scheme,the proposed approach is mesh-free and can be easily applied to high dimensional problems.We present a variety of test problems to show the effectiveness of the learning approach.
基金Support of the DSSI,Grant agencies APVV(No.APVT-20-035404)and RTO-NATO(No.001-AVT-SVK)and VEGA(No.0/0140/08)for this research is gratefully acknowledged.
文摘Trefftz-finite element method(Trefftz-FEM),adaptive cross approximation BEM(ACA BEM)and continuous source function method(CSFM)are used for the simulation of composites reinforced by short fibers(CRSF)with the aim of showing the possibilities of reducing the problem of complicated and important interactions in such composite materials.
