Suppr超能文献

基于时延神经网络的未知时延非线性系统辨识

Identification of nonlinear systems with unknown time delay based on time-delay neural networks.

作者信息

Ren X M, Rad A B

出版信息

IEEE Trans Neural Netw. 2007 Sep;18(5):1536-41. doi: 10.1109/tnn.2007.899702.

Abstract

In this letter, we address the problem of online identification of nonlinear continuous-time systems with unknown time delay based on neural networks (NNs). A novel time-delay NN model with learning algorithm is employed to perform simultaneous system identification and time-delay estimation. The proposed network is an extended version of the time-delay-free dynamical NN. Rigorous stability proof for the identification error is given by means of Lyapunov theory. The simulation studies are provided to demonstrate the performance of the identification algorithm and clarify the theoretical implications.

摘要

在这封信中,我们探讨了基于神经网络(NN)对具有未知时滞的非线性连续时间系统进行在线辨识的问题。采用一种带有学习算法的新型时滞神经网络模型来同时进行系统辨识和时滞估计。所提出的网络是无时滞动态神经网络的扩展版本。借助李雅普诺夫理论给出了辨识误差的严格稳定性证明。通过仿真研究来展示辨识算法的性能并阐明其理论意义。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验