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Inspired by sensing strategies observed in birds and bats, a new attitude control concept of directly using real-time pressure and shear stresses has recently been studied. It was shown that with an array of onboard airflow sensors, small unmanned aircraft systems can promptly respond to airflow changes and improve flight performances. In this paper, a mapping function is proposed to compute aerodynamic moments from the real-time pressure and shear data in a practical and computationally tractable formulation. Since many microscale airflow sensors are embedded on the small unmanned aircraft system surface, it is highly possible that certain sensors may fail. Here, an adaptive control system is developed that is robust to sensor failure as well as other numerical mismatches in calculating real-time aerodynamic moments. The advantages of the proposed method are shown in the following simulation cases: (i) feedback pressure and wall shear data from a distributed array of 45 airflow sensors; (ii) 50% failure of the symmetrically distributed airflow sensor array; and (iii) failure of all the airflow sensors on one wing. It is shown that even if 50% of the airflow sensors have failures, the aircraft is still stable and able to track the attitude commands.
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He et al. (2014) studied this question.
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