Exponential &Epsiv ; -Regulation for Multi-Input Nonlinear Systems Using Neural Networks  

Oleh:

Zhou, Shaosheng ; Lam, J. ; Feng, Gang ; Ho, D. W. C.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 16 no. 6 (Nov. 2005), page 1710-1714.
Topik: non linear; exponential; regulation; multi - input; non linear systems; neural networks

Ketersediaan

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

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Isi artikel

This paper considers the problem of robust exponential e - regulation for a class of multi - input non linear systems with uncertainties. The uncertainties appear not only in the feedback channel but also in the control channel. Under some mild assumptions, an adaptive neural network control scheme is developed such that all the signals of the closed - loop system are semiglobally uniformly ultimately bounded and, under the control scheme with initial data starting in some compact set, the states of the closed - loop system is guaranteed to exponentially converge to an arbitrarily specified & epsi ; - neighborhood about the origin. The important contributions of the present work are that a new exponential uniformly ultimately bounded performance is proposed and that the design parameters and initial condition set can be determined easily. The development generalizes and improves earlier results for the single - input case.

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