NDLI: Finite horizon stochastic optimal control of uncertain linear networked control system

Content Provider	IEEE Xplore Digital Library
Author	Hao Xu Jagannathan, S.
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Missouri Univ. of Sci. & Technol., Rolla, MO, USA (Hao Xu; Jagannathan, S.)
Abstract	In this paper, finite horizon stochastic optimal control issue has been studied for linear networked control system (LNCS) in the presence of network imperfections such as network-induced delays and packet losses by using adaptive dynamic programming (ADP) approach. Due to an uncertainty in system dynamics resulting from network imperfections, the stochastic optimal control design uses a novel adaptive estimator (AE) to solve the optimal regulation of uncertain LNCS in a forward-in-time manner in contrast with backward-in-time Riccati equation-based optimal control with known system dynamics. Tuning law for unknown parameters of AE has been derived. Lyapunov theory is used to show that all the signals are uniformly ultimately bounded (UUB) with ultimate bounds being a function of initial values and final time. In addition, the estimated control input converges to optimal control input within finite horizon. Simulation results are included to show the effectiveness of the proposed scheme.
Starting Page	24
Ending Page	30
File Size	389156
Page Count	7
File Format	PDF
ISBN	9781467359252
ISSN	23251824
DOI	10.1109/ADPRL.2013.6614985
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-04-16
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stochastic Optimal Control Estimation error Adaptive Estimator Finite horizon Adaptive systems Optimal control Packet loss Adaptive Dynamics Programming and Reinforcement learning Delays Networked Control System Equations
Content Type	Text
Resource Type	Article

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