Nonlinear network-induced time delay systems with online dynamic Bayesian learning

This paper presents a new control approach for nonlinear network-induced time delay systems using online reset control, neural networks, and dynamic Bayesian networks. We construct a state-feedback based nominal control to develop a linearized system model. The reset control and neural network are e...

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Bibliographic Details
Published in2009 ICCAS-SICE pp. 4200 - 4205
Main Authors Hyun Cheol Cho, Fadali, M.S., Dae Yeon Yeo, Hyun Tae Han, Kwon Soon Lee
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2009
Subjects
Bayesian methods
Control systems
Delay effects
dynamic Bayesian model
Error correction
NCS
Networked control systems
neural network
Neural networks
Nonlinear control systems
Nonlinear dynamical systems
Predictive control
Predictive models
reset control system
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Summary:This paper presents a new control approach for nonlinear network-induced time delay systems using online reset control, neural networks, and dynamic Bayesian networks. We construct a state-feedback based nominal control to develop a linearized system model. The reset control and neural network are employed to compensate for system error due to time delay effect. Finally, we achieve probabilistic modeling for the networked control system (NCS) using a dynamic Bayesian network (DBN) to estimate future system outputs and devise a predictive control system. Our control methodology is evaluated through numerical simulation by investigating its control performance and comparison to a conventional state feedback control approach.
ISBN:9784907764340
4907764340