Output Feedback Control of Nonlinear Systems Using RBF Neural Networks  

Oleh:

Seshagiri, S. ; Khalil, H. K.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 11 no. 1 (2000), page 69-79.
Topik: non linear; non linear systems; RBF neural networks

Ketersediaan

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

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Isi artikel

An adaptive output feedback control scheme for the output tracking of a class of continuous - time nonlinear plants is presented. An RBF neural network is used to adaptively compensate for the plant nonlinearities. The network weights are adapted using a Lyapunov - based design. The method uses parameter projection, control saturation, and a high -gain observer to achieve semi - global uniform ultimate boundedness. The effectiveness of the proposed method is demonstrated through simulations. The simulations also show that by using adaptive control in conjunction with robust control, it is possible to tolerate larger approximation errors resulting from the use of lower order networks.

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