Geometric control for trajectory‐tracking of a quadrotor UAV with suspended load

Jun-an, Wang; Yuan, Xiaozhuoer; Zhu, Bing

doi:10.1049/cth2.12301

Cited by 10 publications

(5 citation statements)

References 24 publications

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“…[12], the researchers employed an extended state observer (ESO) to estimate not only external disturbances but also internal uncertainties in the quadrotor UAV system. Furthermore, the studies in [13,14] primarily focused on the application of geometric controllers in payload transportation. In Ref.…”

Section: Introductionmentioning

confidence: 99%

“…In Ref. [13], a sophisticated geometric control strategy was implemented, managing dual-loop control for effective trajectory tracking and swing angle stabilization in quadrotor UAVs with suspended loads. The researchers in [14] tackled the challenges posed by elastic cables in similar UAV setups by using geometric control techniques combined with the singular perturbation theory to simulate a system with inelastic cables, thus enhancing control precision.…”

Section: Introductionmentioning

confidence: 99%

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Robust Geometric Control for a Quadrotor UAV with Extended Kalman Filter Estimation

Lei,

Liu,

Wang

2024

Actuators

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This study proposes a robust geometric controller tailored for quadrotor unmanned aerial vehicles (UAVs). The original geometric controller exhibits excellent performance in quadrotor UAV maneuvers. However, as a model-based nonlinear control method, it is sensitive to system model parameters. By integrating a novel extended Kalman filter (EKF)-based estimator for real-time, online estimation of the quadrotor’s inertia parameters, the controller adeptly handles internal uncertainties and external perturbations during flight maneuvers. This approach significantly improves the robustness of the control system against model inaccuracies. Empirical evidence is provided through both simulation and extensive real-world flight tests, demonstrating the controller’s effectiveness and its practical applicability in dynamic environments. The results confirm that this integration substantially enhances system reliability and performance under varied operational conditions.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Geometric Control for a Quadrotor UAV with Extended Kalman Filter Estimation

Lei,

Liu,

Wang

2024

Actuators

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“…While there has been substantial research into the control of single quadrotor suspension systems [11,[19][20][21][22][23][24][25][26], many of these methods exhibit limitations. Much of the existing research predominantly concentrates either on the load [19][20][21] or solely on the quadrotor [11,22,23].…”

Section: Introductionmentioning

confidence: 99%

“…Although this specialized approach ensures effective control of the individual component being studied, it often sacrifices the overall system's dynamics. This can lead to undesirable outcomes such as horizontal position oscillations of the quadrotor or significant swings in the suspended load [24][25][26]. To address these issues comprehensively, there is a pressing need for integrated control strategies that simultaneously consider both the quadrotor and the suspended load.…”

Section: Introductionmentioning

confidence: 99%

Coordinated Control of Quadrotor Suspension Systems Based on Consistency Theory

Chen,

Fan,

Wang

et al. 2023

Aerospace

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This paper designs a cooperative control method for the multi-quadrotor suspension system based on consistency theory and realizes the cooperative formation trajectory tracking control of the multi-quadrotor suspension system by designing a consistent formation cooperative algorithm of virtual piloting and a nonlinear controller. First, a new quadrotor suspension system model is established based on the traditional quadrotor model using the Newton–Euler method. This model can accurately reflect the influence of the load on the quadrotor while obtaining the swing of the load. Then, the vertical and horizontal positions are designed separately based on the quadrotor motion characteristics, and the formation algorithm based on the virtual pilot consistency theory ensures that the final convergence of each position is consistent. An integral backstepping controller and an integral backstepping sliding mode controller are designed for quadrotor position, attitude, and load swing control to achieve accurate and fast quadrotor trajectory tracking control while reducing load swing. The stability of all the controllers is demonstrated using Lyapunov functions. Finally, a multi-quadrotor suspension system formation cooperative simulation experiment is designed to verify the designed control method.

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“…During recent years, the application of unmanned aerial vehicles (UAVs) has acquired a great reputation [1][2][3], particularly the four-rotor UAVs generally noted as QUAVs. This is because the QUAVs can realize complicated tasks such as vertical take-off, landing and hover and they have remarkable agile maneuverability.…”

Section: Introductionmentioning

confidence: 99%

Robust state and output feedback prescribed performance interval type‐3 fuzzy reinforcement learning controller for an unmanned aerial vehicle with actuator saturation

Elhaki

Shojaei

Mohammadzadeh

2022

IET Control Theory & Appl

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This paper presents a novel adaptive reinforcement learning control method with interval type-3 fuzzy neural networks to improve the trajectory tracking control performance of quadrotor unmanned aerial vehicles in challenging flight conditions. The proposed reinforcement learning controller is independent of the system's dynamics, and only relies on measurable signals of the system. An adaptive robust controller in collaboration with the suggested reinforcement learning method is designed to significantly improve the robustness of the control system. The maximum overshoot/undershoot, convergence rate and final tracking accuracy are ensured a priori by the prescribed performance control methodology. To develop the proposed controller and to achieve a high-performance closed-loop system, a high-gain observer is employed in order to estimate the velocity and acceleration of the quadrotor unmanned aerial vehicles system. The uniform ultimate boundedness stability of the proposed control algorithm is achieved by a Lyapunov-based stability analysis. Finally, in the simulation section, it is shown that the presented intelligent controller with the proposed learning algorithm result in a better performance in contrast to the other kind of conventional control techniques.

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Geometric control for trajectory‐tracking of a quadrotor UAV with suspended load

Cited by 10 publications

References 24 publications

Robust Geometric Control for a Quadrotor UAV with Extended Kalman Filter Estimation

Robust Geometric Control for a Quadrotor UAV with Extended Kalman Filter Estimation

Coordinated Control of Quadrotor Suspension Systems Based on Consistency Theory

Robust state and output feedback prescribed performance interval type‐3 fuzzy reinforcement learning controller for an unmanned aerial vehicle with actuator saturation

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