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http://dx.doi.org/10.12989/aas.2020.7.1.001

Fin failure diagnosis for non-linear supersonic air vehicle based on inertial sensors  

Ashrafifar, Asghar (Department of Aerospace Engineering, Sharif University of Technology)
Jegarkandi, Mohsen Fathi (Department of Aerospace Engineering, Sharif University of Technology)
Publication Information
Advances in aircraft and spacecraft science / v.7, no.1, 2020 , pp. 1-17 More about this Journal
Abstract
In this paper, a new model-based Fault Detection and Diagnosis (FDD) method for an agile supersonic flight vehicle is presented. A nonlinear model, controlled by a classical closed loop controller and proportional navigation guidance in interception scenario, describes the behavior of the vehicle. The proposed FDD method employs the Inertial Navigation System (INS) data and nonlinear dynamic model of the vehicle to inform fins damage to the controller before leading to an undesired performance or mission failure. Broken, burnt, unactuated or not opened control surfaces cause a drastic change in aerodynamic coefficients and consequently in the dynamic model. Therefore, in addition to the changes in the control forces and moments, system dynamics will change too, leading to the failure detection process being encountered with difficulty. To this purpose, an equivalent aerodynamic model is proposed to express the dynamics of the vehicle, and the health of each fin is monitored by the value of a parameter which is estimated using an adaptive robust filter. The proposed method detects and isolates fins damages in a few seconds with good accuracy.
Keywords
fin failure detection and diagnosis; model aided inertial navigation; parameter estimation; adaptive robust unscented Kalman filter; missile aerodynamics;
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