A Direct Adaptive Neural-Network Control for Unknown Nonlinear Systems and Its Application  

Oleh:

Wang, Hong ; Noriega, J. R.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 9 no. 1 (1998), page 27-34.
Topik: nonlinear systems; adaptive; neural - network; control; non linear systems; application

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.3 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

In this paper a direct adaptive neural - network control strategy for unknown nonlinear systems is presented. The system considered is described by an unknown NARMA model, and a feedforward neural network is used to learn the system. Taking the neural network as a neural model of the system, control signals are directly obtained by minimizing either the instant difference or the cumulative differences between a set point and the output of the neural model. Since the training algorithm guarantees that the output of the neural model approaches that of the actual system, it is shown that the control signals obtained can also make the real system output close to the set point. An application to a flow - rate control system is included to demonstrate the applicability of the proposed method and desired results are obtained.

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