An optimal control method for linear systems with time delay via recurrent neural networks | ||||
| The International Conference on Electrical Engineering | ||||
| Article 47, Volume 6, 6th International Conference on Electrical Engineering ICEENG 2008, May 2008, Page 1-11 PDF (144.19 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/iceeng.2008.34286 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| M. M. Korjani; S. K.Y. Nikravesh; A. Afshar | ||||
| Amirkabir University of Technology, Hafez Ave, Tehran-Iran. | ||||
| Abstract | ||||
| Abstract: This paper investigates the problem of an optimal control for linear systems with time delay and its solution by means of Hopfield neural networks. First, we discrete the system and make it like a system without disturbance then design a disturbance compensator for the system. Second, the dynamic optimization problem is transformed into a static optimization problem via linear state space analysis methods. The parameters of the Hopfield neural network are adjusted such that the network solves the static quadratic optimization problem yielding the optimal control sequence. The outputs of the neurons of the network represent the values of the optimal control signal in each time step. | ||||
| Keywords | ||||
| time delay; optimal control; Hopfield Neural Networks; disturbance rejection | ||||
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