This paper considers the formation tracking problem under a rigidity framework, where the target formation is specified as a minimally and infinitesimally rigid formation and the desired velocity of the group is avail...This paper considers the formation tracking problem under a rigidity framework, where the target formation is specified as a minimally and infinitesimally rigid formation and the desired velocity of the group is available to only a subset of the agents. The following two cases are considered： the desired velocity is constant, and the desired velocity is timevarying. In the first case, a distributed linear estimator is constructed for each agent to estimate the desired velocity. The velocity estimation and a formation acquisition term are employed to design the control inputs for the agents, where the rigidity matrix plays a central role. In the second case, a distributed non-smooth estimator is constructed to estimate the time-varying velocity, which is shown to converge in a finite time. Theoretical analysis shows that the formation tracking problem can be solved under the proposed control algorithms and estimators. Simulation results are also provided to show the validity of the derived results.展开更多
In this note,we study the state estimation problem for a multi-sensor system subject to multiple packet dropouts.A novel optimal distributed fusion estimator is derived by applying a resending mechanism and a parallel...In this note,we study the state estimation problem for a multi-sensor system subject to multiple packet dropouts.A novel optimal distributed fusion estimator is derived by applying a resending mechanism and a parallel information filtering structure.It is shown that the proposed distributed fusion estimator has smaller estimation error covariance and less computation complexity when compared with the centralised Kalman like estimator with multiple intermittent measurements.展开更多
In this paper,distributed estimation of high-dimensional sparse precision matrix is proposed based on the debiased D-trace loss penalized lasso and the hard threshold method when samples are distributed into different...In this paper,distributed estimation of high-dimensional sparse precision matrix is proposed based on the debiased D-trace loss penalized lasso and the hard threshold method when samples are distributed into different machines for transelliptical graphical models.At a certain level of sparseness,this method not only achieves the correct selection of non-zero elements of sparse precision matrix,but the error rate can be comparable to the estimator in a non-distributed setting.The numerical results further prove that the proposed distributed method is more effective than the usual average method.展开更多
This paper studies a distributed formation problem for non‐holonomic mobile robots.Consideration of the leader dynamics of the robots as non‐ideal,that is,subject to dis-turbances/unmodelled variables,is the disting...This paper studies a distributed formation problem for non‐holonomic mobile robots.Consideration of the leader dynamics of the robots as non‐ideal,that is,subject to dis-turbances/unmodelled variables,is the distinguishing feature of this work.The issue is resolved by a distributed combined disturbance‐and‐leader estimator,allowing for the distributed reconstruction of the leader's signals.The estimator needs to detect the leader's information and disturbance.In order to reject such disturbance and achieve the formation asymptotically,the control law incorporates the smooth estimator's estimate of the leader disturbance.Furthermore,the stability of the total distributed formation control algorithm is also examined using the Lyapunov technique.Finally,to show the viability of the pro-posed theoretical results,simulations and actual experiments are carried out.展开更多
结合干涉雷达的天线结构和二维波达方向(direction of arrival,DOA)估计方法,提出一种基于二维干涉式幅相估计的分布式相参阵盲DOA估计算法。利用二维干涉式幅相估计算法的空间谱和模型阶数选择准则获得目标个数和目标方向余弦的粗估计...结合干涉雷达的天线结构和二维波达方向(direction of arrival,DOA)估计方法,提出一种基于二维干涉式幅相估计的分布式相参阵盲DOA估计算法。利用二维干涉式幅相估计算法的空间谱和模型阶数选择准则获得目标个数和目标方向余弦的粗估计;使用子阵间的相位中心偏移来获得目标方向余弦的精估计;针对分布孔径带来的测角模糊问题,采用双尺度解模糊算法实现分布式阵列的高精度方向估计。仿真结果验证了分布式相参阵的高精度测角性能及所提算法的有效性,也验证了分布阵DOA估计中存在基线模糊门限。展开更多
Proceeded from trimmed Hill estimators and distributed inference, a new distributed version of trimmed Hill estimator for heavy tail index is proposed. Considering the case where the number of observations involved in...Proceeded from trimmed Hill estimators and distributed inference, a new distributed version of trimmed Hill estimator for heavy tail index is proposed. Considering the case where the number of observations involved in each machine can be either the same or different and either fixed or varying to the total sample size, its consistency and asymptotic normality are discussed. Simulation studies are particularized to show the new estimator performs almost in line with the trimmed Hill estimator.展开更多
In this paper,an exponential inequality for weighted sums of identically distributed NOD （negatively orthant dependent） random variables is established,by which we obtain the almost sure convergence rate of which re...In this paper,an exponential inequality for weighted sums of identically distributed NOD （negatively orthant dependent） random variables is established,by which we obtain the almost sure convergence rate of which reaches the available one for independent random variables in terms of Berstein type inequality. As application,we obtain the relevant exponential inequality for Priestley-Chao estimator of nonparametric regression estimate under NOD samples,from which the strong consistency rate is also obtained.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.61473240)
文摘This paper considers the formation tracking problem under a rigidity framework, where the target formation is specified as a minimally and infinitesimally rigid formation and the desired velocity of the group is available to only a subset of the agents. The following two cases are considered： the desired velocity is constant, and the desired velocity is timevarying. In the first case, a distributed linear estimator is constructed for each agent to estimate the desired velocity. The velocity estimation and a formation acquisition term are employed to design the control inputs for the agents, where the rigidity matrix plays a central role. In the second case, a distributed non-smooth estimator is constructed to estimate the time-varying velocity, which is shown to converge in a finite time. Theoretical analysis shows that the formation tracking problem can be solved under the proposed control algorithms and estimators. Simulation results are also provided to show the validity of the derived results.
基金supported by the National Natural Science Foundation of China(61473306).
文摘In this note,we study the state estimation problem for a multi-sensor system subject to multiple packet dropouts.A novel optimal distributed fusion estimator is derived by applying a resending mechanism and a parallel information filtering structure.It is shown that the proposed distributed fusion estimator has smaller estimation error covariance and less computation complexity when compared with the centralised Kalman like estimator with multiple intermittent measurements.
基金partly supported by National Natural Science Foundation of China(Grant Nos.12031016,11971324,11471223)Foundations of Science and Technology Innovation Service Capacity Building,Interdisciplinary Construction of Bioinformatics and Statistics,and Academy for Multidisciplinary Studies,Capital Normal University,Beijing。
文摘In this paper,distributed estimation of high-dimensional sparse precision matrix is proposed based on the debiased D-trace loss penalized lasso and the hard threshold method when samples are distributed into different machines for transelliptical graphical models.At a certain level of sparseness,this method not only achieves the correct selection of non-zero elements of sparse precision matrix,but the error rate can be comparable to the estimator in a non-distributed setting.The numerical results further prove that the proposed distributed method is more effective than the usual average method.
基金The Open Project of Key Laboratory of Industrial Internet of Things&Networked Control,Grant/Award Number:2018FF02Natural Science Foundation of Jiangsu Higher Education Institutions,Grant/Award Number:22KJB510027+1 种基金The Open Research Fund from Guangdong Laboratory of Artificial Intelligence and Digital EconomyNational Natural Science Foundation of China,Grant/Award Numbers:62073088,U1911401。
文摘This paper studies a distributed formation problem for non‐holonomic mobile robots.Consideration of the leader dynamics of the robots as non‐ideal,that is,subject to dis-turbances/unmodelled variables,is the distinguishing feature of this work.The issue is resolved by a distributed combined disturbance‐and‐leader estimator,allowing for the distributed reconstruction of the leader's signals.The estimator needs to detect the leader's information and disturbance.In order to reject such disturbance and achieve the formation asymptotically,the control law incorporates the smooth estimator's estimate of the leader disturbance.Furthermore,the stability of the total distributed formation control algorithm is also examined using the Lyapunov technique.Finally,to show the viability of the pro-posed theoretical results,simulations and actual experiments are carried out.
文摘结合干涉雷达的天线结构和二维波达方向(direction of arrival,DOA)估计方法,提出一种基于二维干涉式幅相估计的分布式相参阵盲DOA估计算法。利用二维干涉式幅相估计算法的空间谱和模型阶数选择准则获得目标个数和目标方向余弦的粗估计;使用子阵间的相位中心偏移来获得目标方向余弦的精估计;针对分布孔径带来的测角模糊问题,采用双尺度解模糊算法实现分布式阵列的高精度方向估计。仿真结果验证了分布式相参阵的高精度测角性能及所提算法的有效性,也验证了分布阵DOA估计中存在基线模糊门限。
文摘Proceeded from trimmed Hill estimators and distributed inference, a new distributed version of trimmed Hill estimator for heavy tail index is proposed. Considering the case where the number of observations involved in each machine can be either the same or different and either fixed or varying to the total sample size, its consistency and asymptotic normality are discussed. Simulation studies are particularized to show the new estimator performs almost in line with the trimmed Hill estimator.
基金Supported by the National Natural Science Foundation of China ( 11061007)
文摘In this paper,an exponential inequality for weighted sums of identically distributed NOD （negatively orthant dependent） random variables is established,by which we obtain the almost sure convergence rate of which reaches the available one for independent random variables in terms of Berstein type inequality. As application,we obtain the relevant exponential inequality for Priestley-Chao estimator of nonparametric regression estimate under NOD samples,from which the strong consistency rate is also obtained.
