Fault accommodation of a class of multivariable nonlinear dynamical systems using a learning approach

被引：163

作者：

Polycarpou, MM ^{[1
]}

机构：

[1] Univ Cincinnati, Dept Elect & Comp Engn & Comp Sci, Cincinnati, OH 45221 USA

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2001年 / 46卷 / 05期

关键词：

fault accommodation; fault diagnosis; learning approach; neural network; nonlinear systems;

D O I：

10.1109/9.920792

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This note presents a learning approach for accommodating faults occurring in a class of nonlinear multi-input-multi-output (MIMO) dynamical systems. Changes in the system dynamics due to a fault are modeled as unknown nonlinear functions of the measurable state variables. The closed-loop stability of the robust fault accommodation scheme is established using Lyapunov redesign methods. A simulation example, based on a model of a jet engine compression system, is used to illustrate the fault accommodation design procedure.

引用

页码：736 / 742

页数：7

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