A Linear Identification Method Applied to a Quadcopter Drone for Stochastic Control Algorithms

Carlos E. D. Nogueira; Antonio S. Silveira; Paulo V. D. Nogueira; Lucas de C. Sodré

doi:10.20906/SBAI-SBSE-2023/4095

Carlos E. D. Nogueira Faculdade de Engenharia Elétrica e Biomédica, Universidade Federal do Pará, PA
Antonio S. Silveira Faculdade de Engenharia Elétrica e Biomédica, Universidade Federal do Pará, PA
Paulo V. D. Nogueira Faculdade de Engenharia Elétrica e Biomédica, Universidade Federal do Pará, PA
Lucas de C. Sodré Faculdade de Engenharia Elétrica e Biomédica, Universidade Federal do Pará, PA

DOI: https://doi.org/10.20906/SBAI-SBSE-2023/4095

Keywords: ARMAX Model, Quadcopter Drone, Linear Systems Identification, Stochastic Control, Extended Least Squares

Abstract

This article addresses the challenge of identifying linear systems for mathematical modeling of a quadcopter drone, with the purpose of utilizing them in predictive and stochastic control algorithms. The approach involves the application of two identification methods, namely the Ordinary Least Squares for ARX systems and the Extended Least Squares for ARMAX systems. The findings indicate that the ARMAX models exhibit superior performance indices and are deemed more appropriate for controller projects.