Advances in Aircraft and Spacecraft Science Volume 4, Number 1, January 2017 , pages 53-64 DOI: https://doi.org/10.12989/aas.2016.4.1.053 |
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Analytical fault tolerant navigation system for an aerospace launch vehicle using sliding mode observer |
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Mahdi Hasani, Jafar Roshanian and A. Majid Khoshnood
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Abstract | ||
Aerospace Launch Vehicles (ALV) are generally designed with high reliability to operate in complete security through fault avoidance practices. However, in spite of such precaution, fault occurring is inevitable. Hence, there is a requirement for on-board fault recovery without significant degradation in the ALV performance. The present study develops an advanced fault recovery strategy to improve the reliability of an Aerospace Launch Vehicle (ALV) navigation system. The proposed strategy contains fault detection features and can reconfigure the system against common faults in the ALV navigation system. For this purpose, fault recovery system is constructed to detect and reconfigure normal navigation faults based on the sliding mode observer (SMO) theory. In the face of pitch channel sensor failure, the original gyro faults are reconstructed using SMO theory and by correcting the faulty measurement, the pitch-rate gyroscope output is constructed to provide fault tolerant navigation solution. The novel aspect of the paper is employing SMO as an online tuning of analytical fault recovery solution against unforeseen variations due to its hardware/software property. In this regard, a nonlinear model of the ALV is simulated using specific navigation failures and the results verified the feasibility of the proposed system. Simulation results and sensitivity analysis show that the proposed techniques can produce more effective estimation results than those of the previous techniques, against sensor failures. | ||
Key Words | ||
sliding mode observer; fault detection and isolation; aerospace launch vehicle | ||
Address | ||
Mahdi Hasani, Jafar Roshanian and A. Majid Khoshnood: Department of Aerospace Engineering, K.N. Toosi university of Technology, Vafadar Blvd, Tehran, Iran | ||