DocumentCode :
1657800
Title :
New method for optimal control and filtering of weakly coupled linear discrete stochastic systems
Author :
Aganovic, Z. ; Gajic, Z. ; Shen, X.
Author_Institution :
Dept. of Electr. & Comput. Eng., Rutgers Univ., Piscataway, NJ, USA
Volume :
1
fYear :
1994
Firstpage :
1
Abstract :
In this paper the algebraic regulator and filter Riccati equations of weakly coupled discrete-time stochastic linear control systems are completely and exactly decomposed into reduced-order continuous-time algebraic Riccati equations corresponding to the subsystems. That is the exact solution of the global discrete algebraic Riccati equation is found in terms of the reduced-order subsystem nonsymmetric continuous-time algebraic Riccati equations. In addition, the optimal global Kalman filter is decomposed into local optimal filters both driven by the system measurements and the system optimal control inputs. As a result, the optimal linear-quadratic Gaussian control problem for weakly coupled linear discrete systems takes the complete decomposition and parallelism between subsystem filters and controllers
Keywords :
Kalman filters; Riccati equations; discrete time systems; linear quadratic Gaussian control; linear systems; matrix algebra; stochastic systems; algebraic regulator; filter Riccati equations; filtering; global Kalman filter; global discrete algebraic Riccati equation; linear discrete stochastic systems; linear-quadratic Gaussian control; optimal control; reduced-order subsystem; weakly coupled systems; Communication system control; Control systems; Eigenvalues and eigenfunctions; Filtering; Nonlinear filters; Optimal control; Parallel processing; Regulators; Riccati equations; Stochastic systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on
Conference_Location :
Lake Buena Vista, FL
Print_ISBN :
0-7803-1968-0
Type :
conf
DOI :
10.1109/CDC.1994.411056
Filename :
411056
Link To Document :
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