期刊名称：Journal of Artificial Intelligence and Soft Computing Research
电子版ISSN：2083-2567
出版年度：2013
卷号：3
期号：3
页码：175-187
DOI：10.2478/jaiscr-2014-0012
出版社：Walter de Gruyter GmbH
摘要：In this paper, the fixed final time adaptive optimal regulation of discrete-time linear systems with unknown system dynamics is addressed. First, by transforming the linear systems into the input/output form, the adaptive optimal control design depends only on the measured outputs and past inputs instead of state measurements. Next, due to the time-varying nature of finite-horizon, a novel online adaptive estimator is proposed by utilizing an online approximator to relax the requirement on the system dynamics. An additional error term corresponding to the terminal constraint is defined and minimized overtime. No policy/value iteration is performed by the novel parameter update law which is updated once a sampling interval. The proposed control design yields an online and forward-in-time solution which enjoys great practical advantages. Stability of the system is demonstrated by Lyapunov analysis while simulation results verify the effectiveness of the propose approach.
