3D Trajectory Tracking Control for a Thrust-Propelled Vehicle with Time-varying Disturbances

Kabiri, Meisam; Atrianfar, Hajar; Menhaj, Mohammad Bagher

doi:10.1007/s12555-018-0331-3

Cited by 5 publications

(2 citation statements)

References 19 publications

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“…On the other hand, in [10] a novel 3D path planning technique to steer a sinusoidal path for a quadrotor is presented. Some scientific research, before resolving the problem of trajectory tracking with a quadrotor, first resolves the problem of the disturbances acting in unmanned aerial vehicles such as in [11], where an estimator considers the sliding mode techniques to attenuate the translational disturbance. In [12], an optimal controller in a quadrotor is applied considering external perturbations in the system and a quadrotor linear mathematical model is considered; that is, the control law is working in some quadrotor operating pue with input constraints to avoid the external disturbances and even is demonstrated finitetime convergence.…”

Section: Introductionmentioning

confidence: 99%

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Trajectory Tracking with Adaptive Robust Control for Quadrotor

et al. 2021

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This work proposes three robust mechanisms based on the MIT rule and the sliding-mode techniques. These robust mechanisms have to tune the gains of an adaptive Proportional-Derivative controller to steer a quadrotor in a predefined trajectory. The adaptive structure is a model reference adaptive control (MRAC). The robust mechanisms proposed to achieve the control objective (trajectory tracking) are MIT rule, MIT rule with sliding mode (MIT-SM), MIT rule with twisting (MIT-Twisting), and MIT rule with high order sliding mode (MIT-HOSM).

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Section: Introductionmentioning

confidence: 99%

“…The mathematical model that defines the UAV in [14] is rotation in SO (3). It is worth mentioning that in [11][12][13][14][15] do not applying any adaptive controller.…”

Section: Introductionmentioning

confidence: 99%