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Robust backpropagation training algorithm for multilayered neural tracking controller

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3 Author(s)
Qing Song ; Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore ; Jizhong Xiao ; Yeng Chai Soh

A robust backpropagation training algorithm with a dead zone scheme is used for the online tuning of the neural-network (NN) tracking control system. This assures the convergence of the multilayer NN in the presence of disturbance. It is proved in this paper that the selection of a smaller range of the dead zone leads to a smaller estimate error of the NN, and hence a smaller tracking error of the NN tracking controller. The proposed algorithm is applied to a three-layered network with adjustable weights and a complete convergence proof is provided. The results can also be extended to the network with more hidden layers

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Neural Networks, IEEE Transactions on  (Volume:10 ,  Issue: 5 )