Title :
Optimal Adaptive Sampled-Data Based Control of Stochastic Systems with Compact Parameter Set
Author_Institution :
Beijing Inst. of Control Eng., China
Abstract :
The problem of the sampled-data (SD) based adaptive linear quadratic Gaussian (LQG) optimal control of linear stochastic continuous-time systems with unknown parameters and stochastic disturbances is considered in this paper. For the case where the parameters belong to a known compact set and only sampled information of the system state is available, an SD-based LQG adaptive control is designed. It is shown that the control law is optimal for the corresponding discretized system, and sub-optimal for the original continuous-time system.
Keywords :
adaptive control; continuous time systems; linear quadratic Gaussian control; sampled data systems; stochastic systems; linear stochastic continuous-time systems; optimal control; sampled-data based adaptive linear quadratic Gaussian control; stochastic disturbances; Adaptive control; Control engineering; Control systems; Cost function; Mathematics; Optimal control; Parameter estimation; Programmable control; Stochastic processes; Stochastic systems; Adaptive Control; LQG Control; Sampled-Data-Based Control; Stochastic System;
Conference_Titel :
Control Conference, 2006. CCC 2006. Chinese
Conference_Location :
Harbin
Print_ISBN :
7-81077-802-1
DOI :
10.1109/CHICC.2006.280659
