Fault detection and reconstruction for a class of nonlinear systems with parametric uncertainties

被引：1

作者：

Wang, Jian-Chen ^{[1
]}

Qi, Xiao-Hui ^{[1
]}

Shan, Gan-Lin ^{[2
]}

机构：

[1] Department of Unmanned Plane Engineering, Ordnance Engineering College, Shijiazhuang

[2] Department of Electronics and Optics Engineering, Ordnance Engineering College, Shijiazhuang

来源：

Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2015年 / 37卷 / 01期

关键词：

Adaptive observer; Augmented cubature Kalman filter (ACKF); Fault reconstruction; Longitudinal model; Parametric uncertainty;

D O I：

10.3969/j.issn.1001-506X.2015.01.25

中图分类号：

学科分类号：

摘要：

Aiming at the obvious aerodynamic parametric uncertainties of aircraft in the full flight envelope, a fault reconstruction method based on a modified adaptive observer is proposed. The adaptive observer is improved by the uncertain parameter estimation process and validated on the longitudinal model of some unmanned vehicle. According to this method, the longitudinal model is described as an affine nonlinear structure with time variant parameters, and the observability of its parameter-augmented model is analyzed. On this basis, to deal with conservatism of the robustness dead zone technique in fault detection and refine the detection sensitivity, aerodynamic parameters are identified on line by the augmented cubature Kalman filter (ACKF) algorithm. Then the parameter estimations are adopted in adaptive observer design. As the Lie derivative based criterion guarantees observability of the object system, the literature restriction that the object system must be within some particular structure is avoided. Based on this, the adaptive fault detection threshold and the fault parameter regulation law are derived, and the convergency of the estimation error is analyzed. Finally, simulations are conducted to testify the availability of this method. ©, 2015, Chinese Institute of Electronics. All right reserved.

引用

页码：155 / 162

页数：7

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