On Iterative Adaptive Dynamic Programming

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.

• Periodical: Applied Mechanics and Materials (Volumes 380-384)
• Pages: 712-715
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.380-384.712
• Online since: August 2013
• Authors: Chang Qing Cui, Yi Qiang Wang, Chun Yan Yang, Bao Sheng Yang
• Keywords: Adaptive Dynamic Programming, Iterative Algorithm, Optimal Control, Time Delay

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