October 30, 2018 / / in cs updates on arXiv.org / with No comments /
This paper presents a controller for the transition maneuver of a tail-sitter drone. The tail-sitter model considers aerodynamic terms whereas the proposed controller considers the time-scale separation between drone attitude and position dynamics. The controller design is based on Lyapunov approach and linear saturation functions. Simulations experiments demonstrate the effectiveness of the derived theoretical results.
Tree-CNN: A Deep Convolutional Neural Network for Lifelong Learning. (arXiv:1802.05800v1 [cs.CV])MPC-Inspired Neural Network Policies for Sequential Decision Making. (arXiv:1802.05803v1 [cs.LG])Horovod: fast and easy distributed deep learning in TensorFlow. (arXiv:1802.05799v1 [cs.LG])End-to-end Analysis and Design of a Drone Flight Controller. (arXiv:1802.05802v1 [cs.SY])Detecting Anomalous Faces with 'No Peeking' Autoencoders. (arXiv:1802.05798v1 [cs.CV])
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