Lie-Group Type Quadcopter Control Design by Dynamics Replacement and the Virtual Attractive-Repulsive Potentials Theory
Simone Fiori,
Luca Bigelli and
Federico Polenta
Additional contact information
Simone Fiori: Department of Information Engineering, Marches Polytechnic University, 60121 Ancona, Italy
Luca Bigelli: Graduate School of Mechatronic Engineering, Politecnico di Torino, 10129 Turin, Italy
Federico Polenta: Graduate School of Automation and Control Engineering, Politecnico di Milano, 20133 Milan, Italy
Mathematics, 2022, vol. 10, issue 7, 1-37
Abstract:
The aim of the present research work is to design a control law for a quadcopter drone based on the Virtual Attractive-Repulsive Potentials (VARP) theory. VARP theory, originally designed to enable path following by a small wheeled robot, will be tailored to control a quadcopter drone, hence allowing such device to learn flight planning. The proposed strategy combines an instance of VARP method to control a drone’s attitude ( SO ( 3 ) -VARP) and an instance of VARP method to control a drone’s spatial location ( R 3 -VARP). The resulting control strategy will be referred to as double-VARP method, which aims at making a drone follow a predefined path in space. Since the model of the drone as well as the devised control theory are formulated on a Lie group, their simulation on a computing platform is performed through a numerical analysis method specifically designed for these kinds of numerical simulations. A numerical simulation analysis is used to assess the salient features of the proposed regulation theory. In particular, resilience against shock-type disturbances are assessed numerically.
Keywords: VARP control theory; feedback control; Lie group; autonomous quadcopter control; path following; virtual potentials; resilience against shock-type disturbance (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:7:p:1104-:d:782261
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