کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
410481 | 679146 | 2009 | 10 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Neural network approximation for periodically disturbed functions and applications to control design Neural network approximation for periodically disturbed functions and applications to control design](/preview/png/410481.png)
This paper addresses the approximation problem of functions affected by unknown periodically time-varying disturbances. By combining Fourier series expansion into multilayer neural network or radial basis function neural network, we successfully construct two kinds of novel approximators, and prove that over a compact set, the new approximators can approximate a continuously and periodically disturbed function to arbitrary accuracy. Then, we apply the proposed approximators to disturbance rejection in the first-order nonlinear control systems with periodically time-varying disturbances, but it is straightforward to extend the proposed design methods to higher-order systems by using adaptive backstepping technique. A simulation example is provided to illustrate the effectiveness of control schemes designed in this paper.
Journal: Neurocomputing - Volume 72, Issues 16–18, October 2009, Pages 3891–3900