Quadrotor stabilization by Fuzzy Kalman Filter

Article type: Research Article

Authors: Paramo, L.A.^a | Garcia, E.C.^a | Meda, J.A.^a | de J. Rubio, J.^{b; *} | Escobedo, J.O.^c | Tapia, R.^a | Hernandez, J.O.^a | Lopez, G.^a | Novoa, J.F.^a | Aguilar, A.^a

Affiliations: [a] SEPI-ESIME Zacatenco, Instituto Politécnico Nacional, Av. IPN, Col. Lindavista, Ciudad de México, México | [b] SEPI-ESIME Azcapotzalco, Instituto Politécnico Nacional, Av. Las Granjas No. 682, Col. Santa Catarina, Ciudad de México, México | [c] SEPI-ESIME Ticomán, Instituto Politécnico Nacional, Av. Ticomán, No. 600, Col. San José Ticomán, Ciudad de México, 07340, México

Correspondence: [*] Corresponding author. J. de J. Rubio, SEPI-ESIME Azcapotzalco, Instituto Politécnico Nacional, Av. Las Granjas No. 682, Col. Santa Catarina, Ciudad de México, 02250, México. E-mail: rubio.josedejesus@gmail.com.

Abstract: In this work, state vector estimation by means of the Fuzzy Kalman Filter (FKF) is used to generate a control signal that stabilizes an unmanned quadrotor aircraft. The framework for fuzzy Kalman Filter methodology has been successfully developed, and in this sense, the FKF is implemented and compared with Kalman Filter (KF) and extended Kalman Filter (EKF). It will be proved that the fuzzy version gives some advantages such as a smaller processing time and a smaller Mean Squared Error (MSE). Finally, these results are shown in graphics and tables.

Keywords: Kalman filtering, quadrotor, fuzzy systems stabilization, control systems

DOI: 10.3233/JIFS-191251

Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 4, pp. 4485-4494, 2020