This paper focuses on a new finite-time convergence disturbance rejection control scheme design for a flexible Timoshenko manipulator subject to extraneous disturbances.To suppress the shear deformation and elastic os...This paper focuses on a new finite-time convergence disturbance rejection control scheme design for a flexible Timoshenko manipulator subject to extraneous disturbances.To suppress the shear deformation and elastic oscillation,position the manipulator in a desired angle,and ensure the finitetime convergence of disturbances,we develop three disturbance observers(DOs)and boundary controllers.Under the derived DOs-based control schemes,the controlled system is guaranteed to be uniformly bounded stable and disturbance estimation errors converge to zero in a finite time.In the end,numerical simulations are established by finite difference methods to demonstrate the effectiveness of the devised scheme by selecting appropriate parameters.展开更多
Target tracking control for wheeled mobile robot(WMR)need resolve the problems of kinematics model and tracking algorithm.High-order sliding mode control is a valid method used in the nonlinear tracking control system...Target tracking control for wheeled mobile robot(WMR)need resolve the problems of kinematics model and tracking algorithm.High-order sliding mode control is a valid method used in the nonlinear tracking control system,which can eliminate the chattering of sliding mode control.Currently there lacks the research of robustness and uncertain factors for high-order sliding mode control.To address the fast convergence and robustness problems of tracking target,the tracking mathematical model of WMR and the target is derived.Based on the finite-time convergence theory and second order sliding mode method,a nonlinear tracking algorithm is designed which guarantees that WMR can catch the target in finite time.At the same time an observer is applied to substitute the uncertain acceleration of the target,then a smooth nonlinear tracking algorithm is proposed.Based on Lyapunov stability theory and finite-time convergence,a finite time convergent smooth second order sliding mode controller and a target tracking algorithm are designed by using second order sliding mode method.The simulation results verified that WMR can catch up the target quickly and reduce the control discontinuity of the velocity of WMR.展开更多
With the widespread application of distributed systems, many problems need to be solved urgently. How to design distributed optimization strategies has become a research hotspot. This article focuses on the solution r...With the widespread application of distributed systems, many problems need to be solved urgently. How to design distributed optimization strategies has become a research hotspot. This article focuses on the solution rate of the distributed convex optimization algorithm. Each agent in the network has its own convex cost function. We consider a gradient-based distributed method and use a push-pull gradient algorithm to minimize the total cost function. Inspired by the current multi-agent consensus cooperation protocol for distributed convex optimization algorithm, a distributed convex optimization algorithm with finite time convergence is proposed and studied. In the end, based on a fixed undirected distributed network topology, a fast convergent distributed cooperative learning method based on a linear parameterized neural network is proposed, which is different from the existing distributed convex optimization algorithms that can achieve exponential convergence. The algorithm can achieve finite-time convergence. The convergence of the algorithm can be guaranteed by the Lyapunov method. The corresponding simulation examples also show the effectiveness of the algorithm intuitively. Compared with other algorithms, this algorithm is competitive.展开更多
This paper proposes a novel neural adaptive performance-constrained synchronization tracking control algorithm for multiple hypersonic flight vehicles(HFVs),which are subject to actuator faults and full-state constrai...This paper proposes a novel neural adaptive performance-constrained synchronization tracking control algorithm for multiple hypersonic flight vehicles(HFVs),which are subject to actuator faults and full-state constraints.The proposed method is based on advanced Lyapunov finite-time stability theory and a sophisticated backstepping design scheme.The longitudinal model of HFV is converted into velocity and altitude subsystems through functional decomposition.Our method presents three significant contributions over the existing state-of-the-art approaches:(a)ensuring finite-time convergence of HFVs systems by guaranteeing that the setting time is lower bounded by a positive constant that is related to the initial states;(b)utilizing a tan-type Barrier Lyapunov function(BLF)to ensure that the synchronization tracking errors of velocity,altitude,flight path angle,angle of attack,and pitch angle rate are maintained within certain performance bounds;and(c)designing a neural adaptive control algorithm and adaptive parameter laws by combining the backstepping design technique and radial basisfunction neural networks(RBFNNs)to handle unknown actuator faults and modeling uncer-tainties.Finally,comparative simulations are conducted to validate the efficacy of the proposed scheme.展开更多
The finite-time convergence problem of an nth nonlinear system with unmatched disturbance is primarily studied in this paper. During the recursive procedure, a new finite-timecontroller is designed and proven by addin...The finite-time convergence problem of an nth nonlinear system with unmatched disturbance is primarily studied in this paper. During the recursive procedure, a new finite-timecontroller is designed and proven by adding a sign function and a power integrator. Meanwhile, a C1 positive definite and proper Lyapunov function, which satisfies the finite-timeLyapunov stability law, is designed. Finally, the designed finite-time controller is appliedto some examples and an application of integrated guidance and control system to testand verify its advantage and practicability.展开更多
In order to achieve accurate interception of high-speed maneuvering targets,this paper presents a relative Line-of-Sight(LOS)velocity based finite-time three-dimensional guidance law design framework,and discusses the...In order to achieve accurate interception of high-speed maneuvering targets,this paper presents a relative Line-of-Sight(LOS)velocity based finite-time three-dimensional guidance law design framework,and discusses the application of fixed-time convergence disturbance observer in this framework.Firstly,a simple Lyapunov function is provided to show that the coupled terms in the relative kinematics can be ignored in the proposed guidance law design framework.Secondly,the realizations of several classical guidance laws are analyzed with the proposed framework,including TPN guidance law,finite-time Input-to-State Stability(ISS)guidance law,and sliding mode guidance law.Thirdly,fixed-time convergence disturbance observers are introduced to design the composite finite-time 3D guidance law,and Lyapunov method is employed to show the stability of the guidance system.Numerical simulations with different scenarios show that the proposed generalized guidance law performs high interception accuracy.展开更多
This paper investigates a time-varying anti-disturbance formation problem for a group of quadrotor aircrafts with time-varying uncertainties and a directed interaction topology.A novel Finite-Time Convergent Extended ...This paper investigates a time-varying anti-disturbance formation problem for a group of quadrotor aircrafts with time-varying uncertainties and a directed interaction topology.A novel Finite-Time Convergent Extended State Observer(FTCESO)based fully-distributed formation control scheme is proposed to enhance the disturbance rejection and the formation tracking performances for networked quadrotors.By adopting the hierarchical control strategy,the multiquadrotor system is separated into two subsystems:the outer-loop cooperative subsystem and the inner-loop attitude subsystem.In the outer-loop subsystem,with the estimation of disturbing forces and uncertain dynamics from FTCESOs,an adaptive consensus theory based cooperative controller is exploited to ensure the multiple quadrotors form and maintain a time-varying pattern relying only on the positions of the neighboring aircrafts.In the inner-loop subsystem,the desired attitude generated by the cooperative control law is stably tracked under a FTCESO-based attitude controller in a finite time.Based on a detailed algorithm to specify the cooperative control protocol,the feasibility condition to achieve the time-varying anti-disturbance formation tracking is derived and the rigorous analysis of the whole closed-loop multi-quadrotor system is given.Some numerical examples are conducted to intuitively demonstrate the effectiveness and the improvements of the proposed control framework.展开更多
For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies ...For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies bionic analytical framework based on the partial differential equation-ordinary differential equation(PDE-ODE)approach.Specifically,by designing a specialized network communication protocol and employing the spatial continuum method for densely distributed agents,this paper models the tracking errors of densely distributed agents as a PDE equivalent to a human disease transmission model,and that of sparsely distributed agents as several ODEs equivalent to the predator population models.The coupling relationship between the PDE and ODE models is established through boundary conditions of the PDE,thereby forming a PDE-ODE-based tracking error model for the considered MASs.Furthermore,by integrating adaptive neural control scheme with the aforementioned biological models,a“Flexible Neural Network”endowed with adaptive and self-stabilized capabilities is constructed,which acts upon the considered MASs,enabling their practical finite-time deployment.Finally,effectiveness of the developed approach is illustrated through a numerical example.展开更多
The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the...The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.展开更多
In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergen...In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.展开更多
This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems(ASSs).The fuzzy logic systems(FLSs)are utilized to learn the unknown non-linear dynamics and an a...This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems(ASSs).The fuzzy logic systems(FLSs)are utilized to learn the unknown non-linear dynamics and an auxiliary system is established.Based on the finite-time stability theory and inverse optimal theory,a fuzzy adaptive inverse finite-time inverse optimal control method is proposed.It is proven that the formulated control approach guarantees the stability of the controlled systems,while ensuring that errors converge to a small neighborhood of zero within finite time.Moreover,the optimized control performance can be achieved.Eventually,the simulation results demonstrate the effectiveness of the proposed fuzzy adaptive finite-time inverse optimal control scheme.展开更多
The adaptive H_(∞) finite-time boundedness control problem is studied for a set of nonlinear singular Hamiltonian system(NSHS)in this article.Under an appropriate adaptive state feedback,the NSHS can be equivalently ...The adaptive H_(∞) finite-time boundedness control problem is studied for a set of nonlinear singular Hamiltonian system(NSHS)in this article.Under an appropriate adaptive state feedback,the NSHS can be equivalently transformed into a differential-algebraic system.Next,it is proved that the state feedback can be used as an adaptive H_(∞) finite-time boundedness controller of NSHS.Finally,the effectiveness of the controller designed is verified by an illustrative example of a nonlinear singular circuit system.展开更多
Intercepting high-maneuverability hypersonic targets in near-space environments poses significant challenges due to their extreme speeds and evasive capabilities.To address these challenges,this study presents an inte...Intercepting high-maneuverability hypersonic targets in near-space environments poses significant challenges due to their extreme speeds and evasive capabilities.To address these challenges,this study presents an integrated approach that combines a Three-Dimensional Finite-Time Optimal Cooperative Guidance Law(FTOC)with an Information Fusion Anti-saturation Predefined-time Observer(IFAPO).The proposed FTOC guidance law employs a nonlinear,non-quadratic finite-time optimal control strategy designed for rapid convergence within the limited timeframes of near-space interceptions,avoiding the need for remaining flight time estimation or linear decoupling inherent in traditional methods.To complement the guidance strategy,the IFAPO leverages multi-source information fusion theory and incorporates anti-saturation mechanisms to enhance target maneuver estimation.This method ensures accurate and real-time prediction of target acceleration while maintaining predefined convergence performance,even under complex interception conditions.By integrating the FTOC guidance law and IFAPO,the approach optimizes cooperative missile positioning,improves interception success rates,and minimizes fuel consumption,addressing practical constraints in military applications.Simulation results and comparative analyses confirm the effectiveness of the integrated approach,demonstrating its capability to achieve cooperative interception of highly maneuvering targets with enhanced efficiency and reduced economic costs,aligning with realistic combat scenarios.展开更多
The rapid development of Internet technology has made“Internet+”a hallmark of the current era.The transformation and development of traditional media into all-media have provided a guiding direction for the developm...The rapid development of Internet technology has made“Internet+”a hallmark of the current era.The transformation and development of traditional media into all-media have provided a guiding direction for the development of campus media.The traditional form of campus media,which mainly consists of campus newspapers and campus radio,can no longer meet the application demands of modern higher education for media.In line with the current media convergence environment,campus media need to actively innovate to achieve their own development and progress in keeping with the times.This article explores the innovation path of campus media in the context of media convergence,analyzing the promotion of campus media innovation by the development of new media,the diversification of campus media innovation,and the effective ways of campus media innovation,in order to promote the realization of the innovation and development goals of campus media in the context of media convergence.展开更多
This study looks at how the Belt and Road Initiative(BRI)has affected the economic convergence of the Central Asian Turkic Republics,China,Pakistan,and their major diplomatic partners in the Silk Road region.Using bet...This study looks at how the Belt and Road Initiative(BRI)has affected the economic convergence of the Central Asian Turkic Republics,China,Pakistan,and their major diplomatic partners in the Silk Road region.Using beta and sigma convergence models over a predetermined time frame,the research evaluates economic alignment trends statistically and looks into how trade openness,FDI,and human capital affect the convergence process.The research attempts to discover larger causes of convergence,such as institutional quality and geopolitical closeness,by combining econometric analysis with regional economic dynamics.The purpose of the results is to provide policy suggestions that will improve equitable and sustainable economic convergence inside the Silk Road circle,promoting international cooperation and growth.展开更多
In this study,we present a deterministic convergence analysis of Gated Recurrent Unit(GRU)networks enhanced by a smoothing L_(1)regularization technique.While GRU architectures effectively mitigate gradient vanishing/...In this study,we present a deterministic convergence analysis of Gated Recurrent Unit(GRU)networks enhanced by a smoothing L_(1)regularization technique.While GRU architectures effectively mitigate gradient vanishing/exploding issues in sequential modeling,they remain prone to overfitting,particularly under noisy or limited training data.Traditional L_(1)regularization,despite enforcing sparsity and accelerating optimization,introduces non-differentiable points in the error function,leading to oscillations during training.To address this,we propose a novel smoothing L_(1)regularization framework that replaces the non-differentiable absolute function with a quadratic approximation,ensuring gradient continuity and stabilizing the optimization landscape.Theoretically,we rigorously establish threekey properties of the resulting smoothing L_(1)-regularizedGRU(SL_(1)-GRU)model:(1)monotonic decrease of the error function across iterations,(2)weak convergence characterized by vanishing gradients as iterations approach infinity,and(3)strong convergence of network weights to fixed points under finite conditions.Comprehensive experiments on benchmark datasets-spanning function approximation,classification(KDD Cup 1999 Data,MNIST),and regression tasks(Boston Housing,Energy Efficiency)-demonstrate SL_(1)-GRUs superiority over baseline models(RNN,LSTM,GRU,L_(1)-GRU,L2-GRU).Empirical results reveal that SL_(1)-GRU achieves 1.0%-2.4%higher test accuracy in classification,7.8%-15.4%lower mean squared error in regression compared to unregularized GRU,while reducing training time by 8.7%-20.1%.These outcomes validate the method’s efficacy in balancing computational efficiency and generalization capability,and they strongly corroborate the theoretical calculations.The proposed framework not only resolves the non-differentiability challenge of L_(1)regularization but also provides a theoretical foundation for convergence guarantees in recurrent neural network training.展开更多
This paper presents a robust finite-time visual servo control strategy for the tracking problem of omni-directional mobile manipulators(OMMs)subject to mismatched disturbances.First,the nonlinear kinematic model of vi...This paper presents a robust finite-time visual servo control strategy for the tracking problem of omni-directional mobile manipulators(OMMs)subject to mismatched disturbances.First,the nonlinear kinematic model of visual servoing for OMMs with mismatched disturbances is explicitly presented to solve the whole-body inverse kinematic problem.Second,a sliding mode observer augmented with an integral terminal sliding mode controller is proposed to handle these uncertainties and ensure that the system converges to a small region around the equilibrium point.The boundary layer technique is employed to mitigate the chattering phenomenon.Furthermore,a strict finite-time Lyapunov stability analysis is conducted.An experimental comparison between the proposed algorithm and a traditional position-based visual servo controller is carried out,and the results demonstrate the superiority of the proposed control algorithm.展开更多
The Lagrangian integral time scale(LITS)is a crucial characteristic for investigating the changes in fluid dynamics induced by the chaotic nature,and the finitetime Lyapunov exponent(FTLE)serves as a key measure in th...The Lagrangian integral time scale(LITS)is a crucial characteristic for investigating the changes in fluid dynamics induced by the chaotic nature,and the finitetime Lyapunov exponent(FTLE)serves as a key measure in the analysis of chaos.In this study,a new LITS model with an explicit theoretical basis and broad applicability is proposed based on the FTLE,along with a verification and evaluation criterion grounded in the Lagrangian velocity correlation coefficient.The model is used to cavitating the flow around a Clark-Y hydrofoil,and the LITS is investigated.It leads to the determination of model constants applicable to cavitating flow.The model is evaluated by the Lagrangian velocity correlation coefficient in comparison with other solution methods.All the results show that the LITS model can offer a new perspective and a new approach for studying the changes in fluid dynamics from a Lagrangian viewpoint.展开更多
The harmonic balance method(HBM)has been widely applied to get the periodic solution of nonlinear systems,however,its convergence rate as well as computation efficiency is dramatically degraded when the system is high...The harmonic balance method(HBM)has been widely applied to get the periodic solution of nonlinear systems,however,its convergence rate as well as computation efficiency is dramatically degraded when the system is highly non-smooth,e.g.,discontinuous.In order to accelerate the convergence,an enriched HBM is developed in this paper where the non-smooth Bernoulli bases are additionally introduced to enrich the conventional Fourier bases.The basic idea behind is that the convergence rate of the HB solution,as a truncated Fourier series,can be improved if the smoothness of the solution becomes finer.Along this line,using non-smooth Bernoulli bases can compensate the highly non-smooth part of the solution and then,the smoothness of the residual part for Fourier approximation is improved so as to achieve accelerated convergence.Numerical examples are conducted on systems with non-smooth restoring and/or external forces.The results confirm that the proposed enriched HBM indeed increases the convergence rate and the increase becomes more significant if more non-smooth bases are used.展开更多
In this paper,the convergence of the split-step theta method for stochastic differential equations is analyzed using stochastic C-stability and stochastic B-consistency.The fact that the numerical scheme,which is both...In this paper,the convergence of the split-step theta method for stochastic differential equations is analyzed using stochastic C-stability and stochastic B-consistency.The fact that the numerical scheme,which is both stochastically C-stable and stochastically B-consistent,is convergent has been proved in a previous paper.In order to analyze the convergence of the split-step theta method(θ∈[1/2,1]),the stochastic C-stability and stochastic B-consistency under the condition of global monotonicity have been researched,and the rate of convergence 1/2 has been explored in this paper.It can be seen that the convergence does not require the drift function should satisfy the linear growth condition whenθ=1/2 Furthermore,the rate of the convergence of the split-step scheme for stochastic differential equations with additive noise has been researched and found to be 1.Finally,an example is given to illustrate the convergence with the theoretical results.展开更多
基金supported in part by National Natural Science Foundation of China(61803109)in part by the Innovative School Project of Education Department of Guangdong(2017KQNCX153)+3 种基金in part by the Science and Technology Planning Project of Guangzhou City(201904010494)in part by the Scientific Research Projects of Guangzhou Education Bureau(202032793)in part by the China Postdoctoral Science Foundation(2019M660463)in part by the Interdisciplinary Research Project for Young Teachers of University of Science and Technology Beijing(FRFIDRY-19-024)。
文摘This paper focuses on a new finite-time convergence disturbance rejection control scheme design for a flexible Timoshenko manipulator subject to extraneous disturbances.To suppress the shear deformation and elastic oscillation,position the manipulator in a desired angle,and ensure the finitetime convergence of disturbances,we develop three disturbance observers(DOs)and boundary controllers.Under the derived DOs-based control schemes,the controlled system is guaranteed to be uniformly bounded stable and disturbance estimation errors converge to zero in a finite time.In the end,numerical simulations are established by finite difference methods to demonstrate the effectiveness of the devised scheme by selecting appropriate parameters.
基金supported by National Natural Science Foundation of China(Grant No.61075081)State Key Laboratory of Robotics Technique and System Foundation,Harbin Institute of Technology,China(Grant No.SKIRS200802A02)
文摘Target tracking control for wheeled mobile robot(WMR)need resolve the problems of kinematics model and tracking algorithm.High-order sliding mode control is a valid method used in the nonlinear tracking control system,which can eliminate the chattering of sliding mode control.Currently there lacks the research of robustness and uncertain factors for high-order sliding mode control.To address the fast convergence and robustness problems of tracking target,the tracking mathematical model of WMR and the target is derived.Based on the finite-time convergence theory and second order sliding mode method,a nonlinear tracking algorithm is designed which guarantees that WMR can catch the target in finite time.At the same time an observer is applied to substitute the uncertain acceleration of the target,then a smooth nonlinear tracking algorithm is proposed.Based on Lyapunov stability theory and finite-time convergence,a finite time convergent smooth second order sliding mode controller and a target tracking algorithm are designed by using second order sliding mode method.The simulation results verified that WMR can catch up the target quickly and reduce the control discontinuity of the velocity of WMR.
文摘With the widespread application of distributed systems, many problems need to be solved urgently. How to design distributed optimization strategies has become a research hotspot. This article focuses on the solution rate of the distributed convex optimization algorithm. Each agent in the network has its own convex cost function. We consider a gradient-based distributed method and use a push-pull gradient algorithm to minimize the total cost function. Inspired by the current multi-agent consensus cooperation protocol for distributed convex optimization algorithm, a distributed convex optimization algorithm with finite time convergence is proposed and studied. In the end, based on a fixed undirected distributed network topology, a fast convergent distributed cooperative learning method based on a linear parameterized neural network is proposed, which is different from the existing distributed convex optimization algorithms that can achieve exponential convergence. The algorithm can achieve finite-time convergence. The convergence of the algorithm can be guaranteed by the Lyapunov method. The corresponding simulation examples also show the effectiveness of the algorithm intuitively. Compared with other algorithms, this algorithm is competitive.
文摘This paper proposes a novel neural adaptive performance-constrained synchronization tracking control algorithm for multiple hypersonic flight vehicles(HFVs),which are subject to actuator faults and full-state constraints.The proposed method is based on advanced Lyapunov finite-time stability theory and a sophisticated backstepping design scheme.The longitudinal model of HFV is converted into velocity and altitude subsystems through functional decomposition.Our method presents three significant contributions over the existing state-of-the-art approaches:(a)ensuring finite-time convergence of HFVs systems by guaranteeing that the setting time is lower bounded by a positive constant that is related to the initial states;(b)utilizing a tan-type Barrier Lyapunov function(BLF)to ensure that the synchronization tracking errors of velocity,altitude,flight path angle,angle of attack,and pitch angle rate are maintained within certain performance bounds;and(c)designing a neural adaptive control algorithm and adaptive parameter laws by combining the backstepping design technique and radial basisfunction neural networks(RBFNNs)to handle unknown actuator faults and modeling uncer-tainties.Finally,comparative simulations are conducted to validate the efficacy of the proposed scheme.
文摘The finite-time convergence problem of an nth nonlinear system with unmatched disturbance is primarily studied in this paper. During the recursive procedure, a new finite-timecontroller is designed and proven by adding a sign function and a power integrator. Meanwhile, a C1 positive definite and proper Lyapunov function, which satisfies the finite-timeLyapunov stability law, is designed. Finally, the designed finite-time controller is appliedto some examples and an application of integrated guidance and control system to testand verify its advantage and practicability.
文摘In order to achieve accurate interception of high-speed maneuvering targets,this paper presents a relative Line-of-Sight(LOS)velocity based finite-time three-dimensional guidance law design framework,and discusses the application of fixed-time convergence disturbance observer in this framework.Firstly,a simple Lyapunov function is provided to show that the coupled terms in the relative kinematics can be ignored in the proposed guidance law design framework.Secondly,the realizations of several classical guidance laws are analyzed with the proposed framework,including TPN guidance law,finite-time Input-to-State Stability(ISS)guidance law,and sliding mode guidance law.Thirdly,fixed-time convergence disturbance observers are introduced to design the composite finite-time 3D guidance law,and Lyapunov method is employed to show the stability of the guidance system.Numerical simulations with different scenarios show that the proposed generalized guidance law performs high interception accuracy.
文摘This paper investigates a time-varying anti-disturbance formation problem for a group of quadrotor aircrafts with time-varying uncertainties and a directed interaction topology.A novel Finite-Time Convergent Extended State Observer(FTCESO)based fully-distributed formation control scheme is proposed to enhance the disturbance rejection and the formation tracking performances for networked quadrotors.By adopting the hierarchical control strategy,the multiquadrotor system is separated into two subsystems:the outer-loop cooperative subsystem and the inner-loop attitude subsystem.In the outer-loop subsystem,with the estimation of disturbing forces and uncertain dynamics from FTCESOs,an adaptive consensus theory based cooperative controller is exploited to ensure the multiple quadrotors form and maintain a time-varying pattern relying only on the positions of the neighboring aircrafts.In the inner-loop subsystem,the desired attitude generated by the cooperative control law is stably tracked under a FTCESO-based attitude controller in a finite time.Based on a detailed algorithm to specify the cooperative control protocol,the feasibility condition to achieve the time-varying anti-disturbance formation tracking is derived and the rigorous analysis of the whole closed-loop multi-quadrotor system is given.Some numerical examples are conducted to intuitively demonstrate the effectiveness and the improvements of the proposed control framework.
基金The National Key R&D Program of China(2021ZD0201300)the National Natural Science Foundation of China(624B2058,U1913602 and 61936004)+1 种基金the Innovation Group Project of the National Natural Science Foundation of China(61821003)the 111 Project on Computational Intelligence and Intelligent Control(B18024).
文摘For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies bionic analytical framework based on the partial differential equation-ordinary differential equation(PDE-ODE)approach.Specifically,by designing a specialized network communication protocol and employing the spatial continuum method for densely distributed agents,this paper models the tracking errors of densely distributed agents as a PDE equivalent to a human disease transmission model,and that of sparsely distributed agents as several ODEs equivalent to the predator population models.The coupling relationship between the PDE and ODE models is established through boundary conditions of the PDE,thereby forming a PDE-ODE-based tracking error model for the considered MASs.Furthermore,by integrating adaptive neural control scheme with the aforementioned biological models,a“Flexible Neural Network”endowed with adaptive and self-stabilized capabilities is constructed,which acts upon the considered MASs,enabling their practical finite-time deployment.Finally,effectiveness of the developed approach is illustrated through a numerical example.
基金supported by Doctoral Scientific Research Starting Foundation of Jingdezhen Ceramic University(Grant No.102/01003002031)Re-accompanying Funding Project of Academic Achievements of Jingdezhen Ceramic University(Grant Nos.215/20506277,215/20506341)。
文摘The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.
基金supported by the National Social Science Fundation(Grant No.21BTJ040)the Project of Outstanding Young People in University of Anhui Province(Grant Nos.2023AH020037,SLXY2024A001).
文摘In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.
基金supported by the National Natural Science Foundation of China under 62173172。
文摘This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems(ASSs).The fuzzy logic systems(FLSs)are utilized to learn the unknown non-linear dynamics and an auxiliary system is established.Based on the finite-time stability theory and inverse optimal theory,a fuzzy adaptive inverse finite-time inverse optimal control method is proposed.It is proven that the formulated control approach guarantees the stability of the controlled systems,while ensuring that errors converge to a small neighborhood of zero within finite time.Moreover,the optimized control performance can be achieved.Eventually,the simulation results demonstrate the effectiveness of the proposed fuzzy adaptive finite-time inverse optimal control scheme.
基金supported by the National Nature Science Foundation of China (61877028, 61773015).
文摘The adaptive H_(∞) finite-time boundedness control problem is studied for a set of nonlinear singular Hamiltonian system(NSHS)in this article.Under an appropriate adaptive state feedback,the NSHS can be equivalently transformed into a differential-algebraic system.Next,it is proved that the state feedback can be used as an adaptive H_(∞) finite-time boundedness controller of NSHS.Finally,the effectiveness of the controller designed is verified by an illustrative example of a nonlinear singular circuit system.
基金supported by the National Natural Science Foundation of China(Grant No.61773142).
文摘Intercepting high-maneuverability hypersonic targets in near-space environments poses significant challenges due to their extreme speeds and evasive capabilities.To address these challenges,this study presents an integrated approach that combines a Three-Dimensional Finite-Time Optimal Cooperative Guidance Law(FTOC)with an Information Fusion Anti-saturation Predefined-time Observer(IFAPO).The proposed FTOC guidance law employs a nonlinear,non-quadratic finite-time optimal control strategy designed for rapid convergence within the limited timeframes of near-space interceptions,avoiding the need for remaining flight time estimation or linear decoupling inherent in traditional methods.To complement the guidance strategy,the IFAPO leverages multi-source information fusion theory and incorporates anti-saturation mechanisms to enhance target maneuver estimation.This method ensures accurate and real-time prediction of target acceleration while maintaining predefined convergence performance,even under complex interception conditions.By integrating the FTOC guidance law and IFAPO,the approach optimizes cooperative missile positioning,improves interception success rates,and minimizes fuel consumption,addressing practical constraints in military applications.Simulation results and comparative analyses confirm the effectiveness of the integrated approach,demonstrating its capability to achieve cooperative interception of highly maneuvering targets with enhanced efficiency and reduced economic costs,aligning with realistic combat scenarios.
文摘The rapid development of Internet technology has made“Internet+”a hallmark of the current era.The transformation and development of traditional media into all-media have provided a guiding direction for the development of campus media.The traditional form of campus media,which mainly consists of campus newspapers and campus radio,can no longer meet the application demands of modern higher education for media.In line with the current media convergence environment,campus media need to actively innovate to achieve their own development and progress in keeping with the times.This article explores the innovation path of campus media in the context of media convergence,analyzing the promotion of campus media innovation by the development of new media,the diversification of campus media innovation,and the effective ways of campus media innovation,in order to promote the realization of the innovation and development goals of campus media in the context of media convergence.
文摘This study looks at how the Belt and Road Initiative(BRI)has affected the economic convergence of the Central Asian Turkic Republics,China,Pakistan,and their major diplomatic partners in the Silk Road region.Using beta and sigma convergence models over a predetermined time frame,the research evaluates economic alignment trends statistically and looks into how trade openness,FDI,and human capital affect the convergence process.The research attempts to discover larger causes of convergence,such as institutional quality and geopolitical closeness,by combining econometric analysis with regional economic dynamics.The purpose of the results is to provide policy suggestions that will improve equitable and sustainable economic convergence inside the Silk Road circle,promoting international cooperation and growth.
基金supported by the National Science Fund for Distinguished Young Scholarship(No.62025602)National Natural Science Foundation of China(Nos.U22B2036,11931015)+2 种基金the Fok Ying-Tong Education Foundation China(No.171105)the Fundamental Research Funds for the Central Universities(No.G2024WD0151)in part by the Tencent Foundation and XPLORER PRIZE.
文摘In this study,we present a deterministic convergence analysis of Gated Recurrent Unit(GRU)networks enhanced by a smoothing L_(1)regularization technique.While GRU architectures effectively mitigate gradient vanishing/exploding issues in sequential modeling,they remain prone to overfitting,particularly under noisy or limited training data.Traditional L_(1)regularization,despite enforcing sparsity and accelerating optimization,introduces non-differentiable points in the error function,leading to oscillations during training.To address this,we propose a novel smoothing L_(1)regularization framework that replaces the non-differentiable absolute function with a quadratic approximation,ensuring gradient continuity and stabilizing the optimization landscape.Theoretically,we rigorously establish threekey properties of the resulting smoothing L_(1)-regularizedGRU(SL_(1)-GRU)model:(1)monotonic decrease of the error function across iterations,(2)weak convergence characterized by vanishing gradients as iterations approach infinity,and(3)strong convergence of network weights to fixed points under finite conditions.Comprehensive experiments on benchmark datasets-spanning function approximation,classification(KDD Cup 1999 Data,MNIST),and regression tasks(Boston Housing,Energy Efficiency)-demonstrate SL_(1)-GRUs superiority over baseline models(RNN,LSTM,GRU,L_(1)-GRU,L2-GRU).Empirical results reveal that SL_(1)-GRU achieves 1.0%-2.4%higher test accuracy in classification,7.8%-15.4%lower mean squared error in regression compared to unregularized GRU,while reducing training time by 8.7%-20.1%.These outcomes validate the method’s efficacy in balancing computational efficiency and generalization capability,and they strongly corroborate the theoretical calculations.The proposed framework not only resolves the non-differentiability challenge of L_(1)regularization but also provides a theoretical foundation for convergence guarantees in recurrent neural network training.
基金supported by the Artificial Intelligence Innovation and Development Special Fund of Shanghai(No.2019RGZN01041)the National Natural Science Foundation of China(No.92048205).
文摘This paper presents a robust finite-time visual servo control strategy for the tracking problem of omni-directional mobile manipulators(OMMs)subject to mismatched disturbances.First,the nonlinear kinematic model of visual servoing for OMMs with mismatched disturbances is explicitly presented to solve the whole-body inverse kinematic problem.Second,a sliding mode observer augmented with an integral terminal sliding mode controller is proposed to handle these uncertainties and ensure that the system converges to a small region around the equilibrium point.The boundary layer technique is employed to mitigate the chattering phenomenon.Furthermore,a strict finite-time Lyapunov stability analysis is conducted.An experimental comparison between the proposed algorithm and a traditional position-based visual servo controller is carried out,and the results demonstrate the superiority of the proposed control algorithm.
基金Project supported by the Key Project of the National Natural Science Foundation of China(No.52336001)the Natural Science Foundation of Zhejiang Province of China(No.LR20E090001)。
文摘The Lagrangian integral time scale(LITS)is a crucial characteristic for investigating the changes in fluid dynamics induced by the chaotic nature,and the finitetime Lyapunov exponent(FTLE)serves as a key measure in the analysis of chaos.In this study,a new LITS model with an explicit theoretical basis and broad applicability is proposed based on the FTLE,along with a verification and evaluation criterion grounded in the Lagrangian velocity correlation coefficient.The model is used to cavitating the flow around a Clark-Y hydrofoil,and the LITS is investigated.It leads to the determination of model constants applicable to cavitating flow.The model is evaluated by the Lagrangian velocity correlation coefficient in comparison with other solution methods.All the results show that the LITS model can offer a new perspective and a new approach for studying the changes in fluid dynamics from a Lagrangian viewpoint.
基金supported by the National Natural Science Foundation of China (Grant No. 12372028)the National Key Research and Development Program of China (Grant No. 2020YFC2201101)the Guangdong Basic and Applied Basic Research Foundation (Grant No.2022A1515011809)。
文摘The harmonic balance method(HBM)has been widely applied to get the periodic solution of nonlinear systems,however,its convergence rate as well as computation efficiency is dramatically degraded when the system is highly non-smooth,e.g.,discontinuous.In order to accelerate the convergence,an enriched HBM is developed in this paper where the non-smooth Bernoulli bases are additionally introduced to enrich the conventional Fourier bases.The basic idea behind is that the convergence rate of the HB solution,as a truncated Fourier series,can be improved if the smoothness of the solution becomes finer.Along this line,using non-smooth Bernoulli bases can compensate the highly non-smooth part of the solution and then,the smoothness of the residual part for Fourier approximation is improved so as to achieve accelerated convergence.Numerical examples are conducted on systems with non-smooth restoring and/or external forces.The results confirm that the proposed enriched HBM indeed increases the convergence rate and the increase becomes more significant if more non-smooth bases are used.
基金Supported by the National Natural Science Foundation of China (Grant No. 12301521)the Natural Science Foundation of Shanxi Province (Grant No. 20210302124081)。
文摘In this paper,the convergence of the split-step theta method for stochastic differential equations is analyzed using stochastic C-stability and stochastic B-consistency.The fact that the numerical scheme,which is both stochastically C-stable and stochastically B-consistent,is convergent has been proved in a previous paper.In order to analyze the convergence of the split-step theta method(θ∈[1/2,1]),the stochastic C-stability and stochastic B-consistency under the condition of global monotonicity have been researched,and the rate of convergence 1/2 has been explored in this paper.It can be seen that the convergence does not require the drift function should satisfy the linear growth condition whenθ=1/2 Furthermore,the rate of the convergence of the split-step scheme for stochastic differential equations with additive noise has been researched and found to be 1.Finally,an example is given to illustrate the convergence with the theoretical results.
