Output Feedback Control of a Quadrotor UAV Using Neural Networks

By Travis Dierks, Sarangapani Jagannathan. IEEE Transactions on Neural Networks, 2010

552 citations recorded by the source corpus.

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Autonomy in materials research: a case study in carbon nanotube growth (2016, background): “Traditional examples include driverless cars,(20) spacecraft(21) and unmanned aerial vehicles.(22,23) In autonomous systems, models of the environment are built up and decisions are exercised based on sensory data.”
Survey of advances in guidance, navigation, and control of unmanned rotorcraft systems (2012, methodology): “There are several works that use ANN to identify rotorcraft dynamic models offline or online, as in Dierks and Jagannathan (2010), but most of these works present simulation results only.”
Energy-Efficient UAV Control for Effective and Fair Communication Coverage: A Deep Reinforcement Learning Approach (2018, background): “Dierks and Jagannathan [19] proposed a new nonlinear controller for UAV using neural networks, which learns complete dynamics of UAVs online, and outputs feedback.”
Autonomous landing of a VTOL UAV on a moving platform using image-based visual servoing (2012, methodology): “A combined controller and observer using neural networks is used in [4] to track reference trajectories.”
Reinforcement Learning for UAV Attitude Control (2018, background): “Notable work by Dierks and Jagannathan [14] proposes an intelligent flight control system constructed with neural networks to learn the quadcopter dynamics, online, to navigate along a specified path.”