Giuseppe Sodero
Physics-Guided neural networks for the robust control of drones.
Rel. Alessandro Rizzo. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2022
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Abstract
Throughout recent History Model-Based controllers dominated the scene of flight controller design and their effectiveness has been proven several times. Despite that, their reliance on the accuracy of the mathematical model used in order to represent real plant might lead to an explosion of the complexity of the problem in case of strongly non-linear systems such as UAVs. In the following work, we are going to propose an alternative approach for the design of flight controllers based on the use of ANN and their capabilities of being universal approximators in order to overcome some of the flaws of standard Model-Based controllers.
We are going to investigate the effectiveness of a mixed approach of both Data and Information Driven techniques using Physics-Guided Neural Networks for the approximation of the real plant dynamics
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