Learning Rules for Neuro-Controller Via Simultaneous Perturbation  

Oleh:

Maeda, Y. ; De Figueiredo, R. J. P.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 8 no. 5 (1997), page 1119-1130.
Topik: controller; learning rules; neuro - controller; perturbation

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

This paper describes learning rules using simultaneous perturbation for a neurocontroller that controls an unknown plant. When we apply a direct control scheme by a neural network, the neural network must learn an inverse system of the unknown plant. In this case, we must know the sensitivity function of the plant using a kind of the gradient method as a learning rule of the neural network. On the other hand, the learning rules described here do not require information about the sensitivity function. Some numerical simulations of a two - link planar arm and a tracking problem for a non linear dynamic plant are shown.

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