Robust Output Feedback Control of Nonlinear Stochastic Systems Using Neural Networks  

Oleh:

Battilotti, S. ; Santis, A. De

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 14 no. 1 (Jan. 2003), page 103-116.
Topik: NEURAL NETWORKS; robust output; non linear stochastic; neural networks

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.8 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

We present an adaptive output feedback controller for a class of uncertain stochastic non linear systems. The plant dynamics is represented as a nominal linear system plus nonlinearities. In turn, these nonlinearities are decomposed into a part, obtained as the best approximation given by neural networks, plus a remaining part which is treated as uncertainties, modeling approximation errors, and neglected dynamics. The weights of the neural network are tuned adaptively by a Lyapunov design. The proposed controller is obtained through robust optimal design and combines together parameter projection, control saturation, and high - gain observers. High performances are obtained in terms of large errors tolerance as shown through simulations.

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