Adaptive Output Feedback Control of Uncertain Nonlienar Systems Using Single-Hidden-Layer Neural Networks  

Oleh:

Nardi, F. ; Hovakimyan, N. ; Calise, A. ; Kim, Nakwan

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 13 no. 6 (2002), page 1420-1431.
Topik: multilayer networks; feedback control; non linear systems; single - hidden - layer; neural networks

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.7A Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

We consider adaptive output feedback control of uncertain non linear systems, in which both the dynamics and the dimension of the regulated system may be unknown. However, the relative degree of the regulated output is assumed to be known. Given a smooth reference trajectory, the problem is to design a controller that forces the system measurement to track it with bounded errors. The classical approach requires a state observer. Finding a good observer for an uncertain nonlinear system is not an obvious task. We argue that it is sufficient to build an observer for the output tracking error. Ultimate boundedness of the error signals is shown through Lyapunov's direct method. The theoretical results are illustrated in the design of a controller for a fourth - order non linear system of relative degree two and a high - bandwidth attitude command system for a model R - 50 helicopter.

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