Regular Papers
International Journal of Control, Automation and Systems 2008; 6(3): 444-452
© The International Journal of Control, Automation, and Systems
Nonlinear Networked Control Systems with Random Nature using Neural Approach and Dynamic Bayesian Networks
We propose an intelligent predictive control approach for a nonlinear networked control system (NCS) with time-varying delay and random observation. The control is given by the sum of a nominal control and a corrective control. The nominal control is determined analytically using a linearized system model with fixed time delay. The corrective control is generated online by a neural network optimizer. A Markov chain (MC) dynamic Bayesian network (DBN) predicts the dynamics of the stochastic system online to allow predictive control design. We apply our proposed method to a satellite attitude control system and evaluate its control performance through computer simulation.
Keywords Dynamic Bayesian network, NCS, neural network, random time-delay.
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Regular Papers
International Journal of Control, Automation and Systems 2008; 6(3): 444-452
Published online June 1, 2008
Copyright © The International Journal of Control, Automation, and Systems.
Nonlinear Networked Control Systems with Random Nature using Neural Approach and Dynamic Bayesian Networks
Hyun Cheol Cho and Kwon Soon Lee*
Dong-A University, Korea
Abstract
We propose an intelligent predictive control approach for a nonlinear networked control system (NCS) with time-varying delay and random observation. The control is given by the sum of a nominal control and a corrective control. The nominal control is determined analytically using a linearized system model with fixed time delay. The corrective control is generated online by a neural network optimizer. A Markov chain (MC) dynamic Bayesian network (DBN) predicts the dynamics of the stochastic system online to allow predictive control design. We apply our proposed method to a satellite attitude control system and evaluate its control performance through computer simulation.
Keywords: Dynamic Bayesian network, NCS, neural network, random time-delay.
Vol. 23, No. 3, pp. 683~972
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