Robust H∞; fault diagnosis for stochastic distribution systems with disturbance rejection performance Online publication date: Sat, 07-Jun-2014
by Lina Yao; Ziyang Yin; Hong Wang
International Journal of Modelling, Identification and Control (IJMIC), Vol. 21, No. 3, 2014
Abstract: The task of robust fault diagnosis of stochastic distribution control (SDC) systems with unknown external disturbance is to use the measured input and the system output probability density function (PDF) to still obtain possible fault information of the system. In this paper, an enhanced robust fault diagnosis scheme is presented for the non-Gaussian stochastic distribution system. A B-spline neural network model is established, where a static neural network is applied to model the output PDFs and a non-linear dynamic model is used to describe the relationships between the input and the weight. The composite observer for SDCs is constructed by combining a fault diagnosis observer with a disturbance observer, with which the fault can be diagnosed and the disturbance can be rejected simultaneously. Lastly, an illustrated example is given to demonstrate the effectiveness of the proposed algorithm, and satisfactory results have been obtained.
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