On Iterative Adaptive Dynamic Programming

Linear system is very seldom in actual control works, so there is more engineering significant of researching on the actual nonlinear system. Time delay phenomenon is the objective phenomenon exists in nature. Neural network based on adaptive dynamic programming principle is selected to implement al...

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Published inApplied Mechanics and Materials Vol. 380-384; pp. 712 - 715
Main Authors Cui, Chang Qing, Yang, Chun Yan, Wang, Yi Qiang, Yang, Bao Sheng
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 30.08.2013
Subjects
Time Delay
Iterative Algorithm
Optimal Control
Adaptive Dynamic Programming
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Abstract Linear system is very seldom in actual control works, so there is more engineering significant of researching on the actual nonlinear system. Time delay phenomenon is the objective phenomenon exists in nature. Neural network based on adaptive dynamic programming principle is selected to implement algorithm. The algorithm contains model network training, H network training for time delay function, critic network training. Before running this iterative algorithm, training the model network first, the model uses a three-layer BP network to realize. Time delay function network H(K) is to approximate the functional relationship between the current control input and the delayed input. The critic network is used to approximate system performance function. The simulation results show that the proposed iterative adaptive dynamic programming can solve for the optimal control of delay nonlinear systems.
AbstractList Linear system is very seldom in actual control works, so there is more engineering significant of researching on the actual nonlinear system. Time delay phenomenon is the objective phenomenon exists in nature. Neural network based on adaptive dynamic programming principle is selected to implement algorithm. The algorithm contains model network training, H network training for time delay function, critic network training. Before running this iterative algorithm, training the model network first, the model uses a three-layer BP network to realize. Time delay function network H(K) is to approximate the functional relationship between the current control input and the delayed input. The critic network is used to approximate system performance function. The simulation results show that the proposed iterative adaptive dynamic programming can solve for the optimal control of delay nonlinear systems.
Author Yang, Bao Sheng
Wang, Yi Qiang
Yang, Chun Yan
Cui, Chang Qing
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Cites_doi 10.1109/tac.2005.861718
10.1016/j.jprocont.2007.10.014
10.1109/titb.2006.884362
10.1109/9.119632
10.1109/61.473361
10.1109/taes.2007.4383603
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Iterative Algorithm
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Adaptive Dynamic Programming
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Snippet Linear system is very seldom in actual control works, so there is more engineering significant of researching on the actual nonlinear system. Time delay...
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