1. Robust backpropagation training algorithm for multilayered neural tracking controller
- Author
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Song, Qing, Xiao, Jizhong, and Soh, Yeng Chai
- Subjects
Algorithms -- Research ,Convergence (Mathematics) -- Research ,Neural networks -- Research ,Robust statistics -- Research ,Tracking systems -- Research ,Business ,Computers ,Electronics ,Electronics and electrical industries - Abstract
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 multilayered 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. Index Terms - Convergence, dead zone, disturbance, robust backpropagation, tracking controller.
- Published
- 1999