NDLI: Event-based optimal regulator design for nonlinear networked control systems

Content Provider	IEEE Xplore Digital Library
Author	Sahoo, Avimanyu Xu, Hao Jagannathan, S.
Copyright Year	2014
Description	Author affiliation: Dept. of Elect. and Comp. Eng. Missouri University of Sc. and Tech. Rolla, USA (Sahoo, Avimanyu; Jagannathan, S.) \|\| Department of Elect. Eng. College of Science and Engineering, Texas A&M - Corpus Christi, Corpus Christi, USA (Xu, Hao)
Abstract	This paper presents a novel stochastic event-based near optimal control strategy to regulate a networked control system (NCS) represented as an uncertain nonlinear continuous time system. An online stochastic actor-critic neural network (NN) based approach is utilized to achieve the near optimal regulation in the presence of network constraints, such as, network induced time-varying delays and random packet losses under event-based transmission of the feedback signals. The transformed nonlinear NCS in discrete-time after the incorporation the delays and packet losses is utilized for the actor-critic NN based controller design. To relax the knowledge of the control coefficient matrix, a NN based identifier is used. Event sampled state vector is utilized as NN inputs and their respective weights are updated non-periodically at the occurrence of events. Further, an event-trigger condition is designed by using the Lyapunov technique to ensure ultimate boundedness of all the closed-loop signals and save network resources and computation. Moreover, policy and value iterations are not utilized for the stochastic optimal regulator design. Finally, the analytical design is verified by using a numerical example by carrying out Monte-Carlo simulations.
Starting Page	1
Ending Page	8
File Size	339556
Page Count	8
File Format	PDF
ISBN	9781479945528
DOI	10.1109/ADPRL.2014.7010634
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-12-09
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	adaptive dynamic programming Optimal control Packet loss Artificial neural networks neural networks networked control systems optimal control Vectors Delays Approximation methods Event-triggered control
Content Type	Text
Resource Type	Article

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