A class of stationary models of singular stochastic control has been studied, in which the state is extended to solution of a class of S.D.E. from Wiener process. The existence of optimal control has been proved in al...A class of stationary models of singular stochastic control has been studied, in which the state is extended to solution of a class of S.D.E. from Wiener process. The existence of optimal control has been proved in all cases under some weaker conditions, and the structure of optimal control may be characterized.展开更多
Based on the optimal fusion algorithm weighted by matrices in the linear minimum variance (LMV) sense, a distributed full-order optimal fusion Kalman filter (DFFKF) is given for discrete-time stochastic singular syste...Based on the optimal fusion algorithm weighted by matrices in the linear minimum variance (LMV) sense, a distributed full-order optimal fusion Kalman filter (DFFKF) is given for discrete-time stochastic singular systems with multiple sensors, which involves the inverse of a high-dimension matrix to compute matrix weights. To reduce the computational burden, a distributed reduced-order fusion Kalman filter (DRFKF) is presented, which involves in parallel the inverses of two relatively low-dimension matrices to compute matrix weights. A simulation example shows the effectiveness.展开更多
Stochastic stability analysis and control synthesis problems are studied for a class of nonhomogeneous Markovian jump discretetime singular systems( MJDSS). The time-varying character is considered to be the model in ...Stochastic stability analysis and control synthesis problems are studied for a class of nonhomogeneous Markovian jump discretetime singular systems( MJDSS). The time-varying character is considered to be the model in a polytopic sense. Based on the parameter dependent stochastic Lyapunov functional and the matrix analysis techniques, sufficient criteria are derived to ensure regularity, causality and stochastic stability of the closed-loop singular system in terms of linear matrix inequalities. Finally,one example is provided to illustrate the effectiveness of our results.展开更多
在具有控制输入和动态噪声与观测噪声相关的情况下,给出线性随机系统的集值滤波方程;利用矩阵分解和系统变换的技巧,得到广义随机系统的集值滤波方程.这种状态估计方法适用于初始状态均值位于一个凸集之中的随机系统.与传统K a lm an滤...在具有控制输入和动态噪声与观测噪声相关的情况下,给出线性随机系统的集值滤波方程;利用矩阵分解和系统变换的技巧,得到广义随机系统的集值滤波方程.这种状态估计方法适用于初始状态均值位于一个凸集之中的随机系统.与传统K a lm an滤波产生单个条件分布不同,这里的集值滤波给出一个条件分布的凸集.展开更多
Based on the theory of Bayes forecasting, this paper mainly deals with the problem onthe state estimation for singular discrete-time stochastic linear system. And a new approach to optimalfiltering-linear Bayes estima...Based on the theory of Bayes forecasting, this paper mainly deals with the problem onthe state estimation for singular discrete-time stochastic linear system. And a new approach to optimalfiltering-linear Bayes estimation (LBE) has been proposed.展开更多
Using theory of Bayesian Dynamic Models and Forecasting , this paper mainly deals with the problem on state estimation for singular discrete time stochastic linear system. And a new method of state estimation l...Using theory of Bayesian Dynamic Models and Forecasting , this paper mainly deals with the problem on state estimation for singular discrete time stochastic linear system. And a new method of state estimation linear Bayes estimation (LBE for short) has been proposed.展开更多
基金Supported by the National Science Foundation of China.
文摘A class of stationary models of singular stochastic control has been studied, in which the state is extended to solution of a class of S.D.E. from Wiener process. The existence of optimal control has been proved in all cases under some weaker conditions, and the structure of optimal control may be characterized.
基金Supported by National Natural Science Foundation of P. R. China (60504034) Youth Foundation of Heilongjiang Province (QC04A01) Outstanding Youth Foundation of Heilongjiang University (JC200404)
文摘Based on the optimal fusion algorithm weighted by matrices in the linear minimum variance (LMV) sense, a distributed full-order optimal fusion Kalman filter (DFFKF) is given for discrete-time stochastic singular systems with multiple sensors, which involves the inverse of a high-dimension matrix to compute matrix weights. To reduce the computational burden, a distributed reduced-order fusion Kalman filter (DRFKF) is presented, which involves in parallel the inverses of two relatively low-dimension matrices to compute matrix weights. A simulation example shows the effectiveness.
基金National Natural Science Youth Foundation of China(No.61503238)National Natural Science Foundation of China(No.61673257)
文摘Stochastic stability analysis and control synthesis problems are studied for a class of nonhomogeneous Markovian jump discretetime singular systems( MJDSS). The time-varying character is considered to be the model in a polytopic sense. Based on the parameter dependent stochastic Lyapunov functional and the matrix analysis techniques, sufficient criteria are derived to ensure regularity, causality and stochastic stability of the closed-loop singular system in terms of linear matrix inequalities. Finally,one example is provided to illustrate the effectiveness of our results.
基金Supported by the National Natural Science Foundation of China(11071001)the Doctoral Fund of Ministry of Education of China(20093401110001)+1 种基金the Key Project of Chinese Ministry ofEducation(205068)the Major Program of Educational Commission of Anhui Province of China(KJ2010ZD02)
文摘Based on the theory of Bayes forecasting, this paper mainly deals with the problem onthe state estimation for singular discrete-time stochastic linear system. And a new approach to optimalfiltering-linear Bayes estimation (LBE) has been proposed.
文摘Using theory of Bayesian Dynamic Models and Forecasting , this paper mainly deals with the problem on state estimation for singular discrete time stochastic linear system. And a new method of state estimation linear Bayes estimation (LBE for short) has been proposed.
