Alanis Alma Y, Sanchez Edgar N, Loukianov Alexander G, Perez Marco A
Centro Universitario de Ciencias Exactas e Ingenierías, Universidad de Guadalajara, Jalisco 44430, Mexico.
IEEE Trans Neural Netw. 2011 Mar;22(3):497-505. doi: 10.1109/TNN.2010.2103322. Epub 2011 Jan 17.
A nonlinear discrete-time neural observer for discrete-time unknown nonlinear systems in presence of external disturbances and parameter uncertainties is presented. It is based on a discrete-time recurrent high-order neural network trained with an extended Kalman-filter based algorithm. This brief includes the stability proof based on the Lyapunov approach. The applicability of the proposed scheme is illustrated by real-time implementation for a three phase induction motor.
针对存在外部干扰和参数不确定性的离散时间未知非线性系统，提出了一种非线性离散时间神经观测器。它基于一个采用基于扩展卡尔曼滤波器算法训练的离散时间递归高阶神经网络。本简报包括基于李雅普诺夫方法的稳定性证明。通过对三相感应电动机的实时实现，说明了所提方案的适用性。
