JSEA  Vol.5 No.4 , April 2012
Lyapunov-Based Dynamic Neural Network for Adaptive Control of Complex Systems
In this paper, an adaptive neuro-control structure for complex dynamic system is proposed. A recurrent Neural Network is trained-off-line to learn the inverse dynamics of the system from the observation of the input-output data. The direct adaptive approach is performed after the training process is achieved. A lyapunov-Base training algorithm is proposed and used to adjust on-line the network weights so that the neural model output follows the desired one. The simulation results obtained verify the effectiveness of the proposed control method.

Cite this paper
F. Zouari, K. Ben Saad and M. Benrejeb, "Lyapunov-Based Dynamic Neural Network for Adaptive Control of Complex Systems," Journal of Software Engineering and Applications, Vol. 5 No. 4, 2012, pp. 225-248. doi: 10.4236/jsea.2012.54028.
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