Information states in stochastic control and filtering: a Liealgebraic theoretic approach

Charalambous C.D.; Elliott R.J.

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Information states in stochastic control and filtering: a Liealgebraic theoretic approach

机译：随机控制和过滤中的信息状态：Lielegebraic理论方法

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The purpose of the paper is two-fold: (i) to introduce the sufficient statistic algebra which is responsible for propagating the sufficient statistics, or information state, in the optimal control of stochastic systems and (ii) to apply certain Lie algebraic methods and gauge transformations, widely used in nonlinear control theory and quantum physics, to derive new results concerning finite dimensional controllers. This enhances our understanding of the role played by the sufficient statistics. The sufficient statistic algebra enables us to determine a priori whether there exist finite-dimensional controllers; it also enables us to classify all finite-dimensional controllers. Relations to minimax dynamic games are delineated

机译：本文的目的有两个：（i）引入足够的统计代数，该代数负责传播随机系统的最优控制中的足够的统计量或信息状态；（ii）应用某些李代数方法，以及规范变换已广泛用于非线性控制理论和量子物理学中，以得出有关有限维控制器的新结果。这加深了我们对足够的统计数据所起的作用的理解。足够的统计代数使我们能够先验地确定是否存在有限维控制器。它还使我们能够对所有有限维控制器进行分类。描述了与极小极大动态游戏的关系

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《IEEE Transactions on Automatic Control》 |2000年第4期|p.653-674|共22页
作者
Charalambous C.D.; Elliott R.J.;
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正文语种 eng
中图分类自动化系统;
关键词
Lie algebras; filtering theory; game theory; multidimensional systems; optimal control; stochastic systems; Lie algebraic theoretic approach; finite dimensional controllers; gauge transformations; information state; information states; minimax dynamic games; stochas;

机译：李代数;过滤理论;博弈论;多维系统;最优控制;随机系统;李代数理论方法;有限维控制器;量表变换;信息状态;信息状态;最小极大动态博弈;随机;

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专利

1. Information states in stochastic control and filtering: a Lie algebraic theoretic approach [J] . Charalambous C.D., Elliott R.J. IEEE Transactions on Automatic Control . 2000,第4期

机译：随机控制和过滤中的信息状态：李代数理论方法
2. Optimal Control and Filtering of Weakly Coupled Linear Discrete-Time Stochastic Systems by the Eigenvector Approach [J] . Naser Prljaca, Zoran Gajic Automatika . 2008,第3a4期

机译：基于特征向量法的弱耦合线性离散随机系统的最优控制与滤波
3. A Control-Theoretic Approach for Efficient Design of Filters in DAC and Digital Audio Amplifiers [J] . Konstantinos Tsakalis, Nikolaos Vlassopoulos, George Lentaris, Circuits, systems and signal processing . 2011,第2期

机译：一种控制理论方法，可有效设计DAC和数字音频放大器中的滤波器
4. Minimum Entropy Filtering for Networked Control Systems viaInformation Theoretic Learning Approach [C] . Jianhua Zhang, Lei Cai, Hong Wang International Conference on Modelling, Identification and Control . 2010

机译：网络控制系统的最小熵滤波，虚拟学习方法
5. A Kalman filtering approach to stochastic tomography. [D] . Luo, Der-Shan. 1991

机译：卡尔曼滤波方法用于随机层析成像。
6. A stochastic filtering approach to recover strain images from quasi-static ultrasound elastography [O] . Minhua Lu, Dan Wu, Wan-hua Lin, 2010

机译：一种从准静态超声弹性成像恢复应变图像的随机滤波方法
7. Nonlinear Filtering and Large Deviations: A PDE-Control Theoretic Approach. [O] . James, Matthew R., Baras, John S. 1987

机译：非线性滤波和大偏差：PDE控制理论方法。
8. Nonlinear Filtering and Large Deviations: A PDE-Control Theoretic Approach [R] . James, M. R., Baras, J. S. 1987

机译：非线性滤波和大偏差：pDE控制理论方法

Information states in stochastic control and filtering: a Liealgebraic theoretic approach

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