2014
DOI: 10.9746/sicetr.50.784
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Adaptive H^|^infin; Tracking Control for Quad-rotor Helicopters Based on Input-output Linearization

Abstract: This paper considers the problem of controlling both the position and the attitude of a quad-rotor helicopter. The quad-rotor helicopter is described by a set of nonlinear equations and some parameters of the dynamics are subjected to uncertainties. This paper proposes a new input-output linearization method based on an adaptive law, and presents a new adaptive tracking controller with on-line parameter estimation to make the tracking error zero asymptotically for the position and the yaw angle. The design pro… Show more

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Cited by 3 publications
(1 citation statement)
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“…They also use a nonlinear Hinfinity control scheme on quadrotor helicopter that has been modified in order to obtain coupling between longitudinal and lateral movement with the roll and pitch motions to follow a given reference path [12,13]. Keita Mori, et al, [14] using standard H-Infinity control to reduce disturbance sensitivity of the quad-rotor helicopter.They control both the position and the altitude of the quadrotor model using a new input-output linearization method. Taesam Kang, et al, [15] designed a robust H-Infinity attitude controller of linear models quadrotor obtained from the estimated input -output data using Prediction Error Minimation.…”
mentioning
confidence: 99%
“…They also use a nonlinear Hinfinity control scheme on quadrotor helicopter that has been modified in order to obtain coupling between longitudinal and lateral movement with the roll and pitch motions to follow a given reference path [12,13]. Keita Mori, et al, [14] using standard H-Infinity control to reduce disturbance sensitivity of the quad-rotor helicopter.They control both the position and the altitude of the quadrotor model using a new input-output linearization method. Taesam Kang, et al, [15] designed a robust H-Infinity attitude controller of linear models quadrotor obtained from the estimated input -output data using Prediction Error Minimation.…”
mentioning
confidence: 99%