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Nonlinear Network-Induced Time Delay Systems With Stochastic Learning

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2 Author(s)
Hyun Cheol Cho ; Sch. of Electr. & Electron. Eng., Ulsan Coll., Ulsan, South Korea ; Fadali, M.S.

This paper presents a new control approach for nonlinear network-induced time delay systems by combining online reset control, neural networks, and dynamic Bayesian networks. We use feedback linearization to construct a nominal control for the system then use reset control and a neural network to compensate for errors due to the time delay. Finally, we obtain a stochastic model of the Networked Control System (NCS) using a Dynamic Bayesian Network (DBN) and use it to design a predictive control. We apply our control methodology to a nonlinear inverted pendulum and evaluate its performance through numerical simulations. We also test our approach with real-time experiments on a dc motor-load NCS with wireless communication implemented using a Ubiquitous Sensor Network (USN). Both the simulation and experimental results demonstrate the efficacy of our control methodology.

Published in:

Control Systems Technology, IEEE Transactions on  (Volume:19 ,  Issue: 4 )

Date of Publication:

July 2011

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