Findings in Nonlinear Research Reported from G.X. Wen and Co-Researchers.

According to the authors of a study from Liaoning, People's Republic of China, "Based on the backstepping technique, an adaptive neural network (NN) based output feedback controller is proposed to achieve a desired tracking performance for a class of discrete-time nonlinear systems, which are represented in non-strict-feedback form. The neural networks are utilized to approximate unknown functions in the systems."

"The adaptive output feedback controller needs only to adjust less adaptive parameters, therefore it is clear that the proposed approach can reduce on-line computation burden. It is proven that all the signals in the closed-loop system are semi-global uniformly ultimately bounded (SGUUB) and the tracking error converges to a small neighborhood of zero by choosing the design parameters appropriately," wrote G.X. Wen and colleagues.

The researchers concluded: "A simulation example is used to verify the effectiveness of the proposed approach."

Wen and colleagues published their study in Nonlinear Dynamics (Adaptive neural output feedback control of nonlinear discrete-time systems. Nonlinear Dynamics, 2011;65(1-2):65-75).

For more information, contact G.X. Wen, Liaoning University Technology, School Science, Jinzhou 121001, Liaoning, People's Republic of China.

Publisher contact information for the journal Nonlinear Dynamics is: Springer, Van Godewijckstraat 30, 3311 Gz Dordrecht, Netherlands.

Keywords: City:Liaoning, Country:People's Republic of China, Region:Asia, Nonlinear Research

This article was prepared by Internet Networks & Communications editors from staff and other reports. Copyright 2011, Internet Networks & Communications via VerticalNews.com.