Title :
Information evolutions in the linear stochastic control systems
Author :
Huang, Tongyuan ; Chen, Badong
Author_Institution :
Inst. of Comput. Sci. & Eng., Chongqing Inst. of Technol., Chongqing
Abstract :
We study the evolution law of information measure in the stochastic control system. For linear Gaussian systems, we derive the exact evolution formulas for the entropy, mutual information, divergence, and the components dependent degree (CDD) of the state vectors. A simple example is used to illustrate how the feedback will influence the information evolutions. The view of information evolution seems very useful in the analysis and design of control system.
Keywords :
Gaussian processes; control system analysis; control system synthesis; entropy; feedback; linear systems; stochastic systems; component dependent degree; control system analysis; control system design; entropy; feedback; information evolution; linear Gaussian system; linear stochastic control system; mutual information; state vector; Computer science; Control systems; Entropy; Feedback; Information theory; Intelligent control; Mutual information; Probability density function; Stochastic systems; Vectors; divergence; entropy; mutual information; stochastic control system;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4593463
