Output Feedback Tracking Control of an Underactuated Quad-Rotor UAV

Lee, Dongbin; Burg, Timothy C.; Xian, Bin; Dawson, D.M.

doi:10.1109/acc.2007.4282556

Cited by 28 publications

(13 citation statements)

References 10 publications

(14 reference statements)

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“…The controller provides good performances for the set of parameters with respect stability and tracking. The results are proved to be efficient, compared to the ones usually implemented in such an UAV [3], [5], [8]. The paper does not bring the comparison of existing solutions.…”

Section: Discussionmentioning

confidence: 97%

“…Due to the progress in sensing technologies, power storage and miniature actuators, the cost and size reductions for mini-UAV lead professionals and researchers to several applications [1], [2], [3], [4]. Research activities focused on modelling and control design of this aerial platform [5], [6]. More precisely, the dynamic description of the quadrotor in mechanical and aerodynamic senses is still a sensitive subject.…”

Section: Introductionmentioning

confidence: 99%

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Robust control for an off-centered quadrotor

Raharijaona

Bateman

2011

2011 19th Mediterranean Conference on Control &Amp; Automation (MED)

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Abstract-The development of quadrotor unmanned aerial vehicles -UAVs-in potential civil applications is conditioned by the embedded elements such as removable payload, miniature actuators, sensors and power storage. As simple as the structure of the quarotor is, the dynamic behavior is complex. The paper details a model of a quadrotor which considers the effects of the location of the center of gravity and the gyroscopic torques due to the derivative of the speed propellers. A simple control law in order to regulate the angular velocities and to track angular references is designed. Time domain constraints and parameters which belong to a polytope define the basis of the regulator synthesis. The relevance of the study is fulfilled thanks to numerical simulations and experimental plateform is presented.

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Section: Discussionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Robust control for an off-centered quadrotor

Raharijaona

Bateman

2011

2011 19th Mediterranean Conference on Control &Amp; Automation (MED)

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“…For the aerial vehicles even flying at moderate velocities, neglecting the aerodynamic forces will lead to the instability of the overall control system. To address the trajectory tracking control problem of the aerial robots with the nonlinear aerodynamic damping, up to now, some interesting results have been obtained in [15]- [19]. In [17], the aerodynamic forces, which can be linearly parameterized, were included in the considered dynamic model of the underactuated quadrotor, and an observer-based adaptive control approach was developed in [19] to guarantee a good tracking performance of the controlled helicopter.…”

Section: Introductionmentioning

confidence: 99%

“…To address the trajectory tracking control problem of the aerial robots with the nonlinear aerodynamic damping, up to now, some interesting results have been obtained in [15]- [19]. In [17], the aerodynamic forces, which can be linearly parameterized, were included in the considered dynamic model of the underactuated quadrotor, and an observer-based adaptive control approach was developed in [19] to guarantee a good tracking performance of the controlled helicopter. Furthermore, the coupling effect of the aerodynamic forces and the blade flap makes that the uncertain dynamics of the helicopter studied in [15] cannot be linearly parameterized.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Position/Attitude Tracking Control of Aerial Robot With Unknown Inertial Matrix Based on a New Robust Neural Identifier

Lai

Liu

Zhang

et al. 2016

IEEE Trans. Neural Netw. Learning Syst.

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This paper presents a novel adaptive controller for controlling an autonomous helicopter with unknown inertial matrix to asymptotically track the desired trajectory. To identify the unknown inertial matrix included in the attitude dynamic model, this paper proposes a new structural identifier that differs from those previously proposed in that it additionally contains a neural networks (NNs) mechanism and a robust adaptive mechanism, respectively. Using the NNs to compensate the unknown aerodynamic forces online and the robust adaptive mechanism to cancel the combination of the overlarge NNs compensation error and the external disturbances, the new robust neural identifier exhibits a better identification performance in the complex flight environment. Moreover, an optimized algorithm is included in the NNs mechanism to alleviate the burdensome online computation. By the strict Lyapunov argument, the asymptotic convergence of the inertial matrix identification error, position tracking error, and attitude tracking error to arbitrarily small neighborhood of the origin is proved. The simulation and implementation results are provided to evaluate the performance of the proposed controller.

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Model‐assisted extended state observer and dynamic surface control–based trajectory tracking for quadrotors via output‐feedback mechanism

Shao

Liu

et al. 2018

Intl J Robust & Nonlinear

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Summary In this paper, an output‐feedback trajectory tracking controller for quadrotors is presented by integrating a model‐assisted extended state observer (ESO) with dynamic surface control. The quadrotor dynamics are described by translational and rotational loops with lumped disturbances to promote the hierarchical control design. Then, by exploiting the structural property of the quadrotor, a model information–assisted high‐order ESO that relies only on position measurements is designed to estimate not only the unmeasurable states but also the lumped disturbances in the rotational loop. In addition, to account for the problem of “explosion of complexity” inherent in hierarchical control, the output feedback–based trajectory tracking and attitude stabilization laws are respectively synthesized by utilizing dynamic surface control and the corresponding estimated signals provided by the ESO. The stability analysis is given, showing that the output‐feedback trajectory tracking controller can ensure the ultimate boundedness of all signals in the closed‐loop system and make the tracking errors arbitrarily small. Finally, flight simulations with respect to an 8‐shaped trajectory command are performed to verify the effectiveness of the proposed scheme in obtaining the stable and accurate trajectory tracking using position measurements only.

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Output Feedback Tracking Control of an Underactuated Quad-Rotor UAV

Cited by 28 publications

References 10 publications

Robust control for an off-centered quadrotor

Robust control for an off-centered quadrotor

Adaptive Position/Attitude Tracking Control of Aerial Robot With Unknown Inertial Matrix Based on a New Robust Neural Identifier

Model‐assisted extended state observer and dynamic surface control–based trajectory tracking for quadrotors via output‐feedback mechanism

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