Abstract
Research into the autonomy of small Unmanned Aerial Vehicles (UAVs), and especially on Vertical Take Off and Landing (VTOL) systems has intensified significantly in recent years. This paper develops a generic model of a VTOL UAV in symbolic form. The novelty of this work stems from the designed Model Predictive Control (MPC) algorithm based on this symbolic model. The MPC algorithm is compared with a state-of-the-art Linear Quadratic Regulator algorithm in attitude rate acquisition and its more accurate performance and robustness to noise is demonstrated. Results for the controllers designed for each of the aircraft’s angular rates are presented in response to input disturbances.
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Acknowledgements
The authors gratefully acknowledge the support from the UK EPSRC under grant number EP/M506618/1.
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Douthwaite, J.A., Mihaylova, L.S., Veres, S.M. (2016). Enhancing Autonomy in VTOL Aircraft Based on Symbolic Computation Algorithms. In: Alboul, L., Damian, D., Aitken, J. (eds) Towards Autonomous Robotic Systems. TAROS 2016. Lecture Notes in Computer Science(), vol 9716. Springer, Cham. https://doi.org/10.1007/978-3-319-40379-3_10
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DOI: https://doi.org/10.1007/978-3-319-40379-3_10
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