Extended Discrete-Time Quasi-Sliding Mode Control for VTOL UAV in the Presence of Uncertain Disturbances

Imran, Imil Hamda; Memon, Azhar M.; Kurtuluş, Dilek Funda; Goli, Srikanth; Alhems, Luai M.

doi:10.1109/access.2023.3280543

Cited by 4 publications

(2 citation statements)

References 38 publications

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“…Similar to the X-position tracker, the Y-position tracker also demonstrated a remarkable stabilization time of two seconds, as depicted in figure 13. In contrast, previous researchers [44] required up to thirty seconds to achieve the same level of settling. This notable improvement can be attributed to our diligent parameter selection and the inherent self-optimization capability of the MPC controller.…”

Section: Linear Responsesmentioning

confidence: 84%

“…To see the effectiveness of the controller in stabilizing the input, system parameters used by linear quadratic regulator [44] and sliding mode controller [45] are used for comparison. Figure 10 depicts the input response comparative performance of previous works so that due to its self-optimization capability, the MPC controller designed has stabilized the system's input with in short period of time.…”

Section: Validation With Previous Workmentioning

confidence: 99%

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Aerodynamic modeling and performance analysis of model predictive controller for fixed wing vertical takeoff and landing unmanned aerial vehicle

Getachew,

Zeleke

2024

Eng. Res. Express

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TThis research focuses mainly on the aerodynamic modelling and performance analysis of a model predictive controller for a hybrid fixed-wing vertical takeoff and landing of unmanned aerial vehicle. The aerodynamics, which comprises several aerodynamic characteristics including the lift, drag, and thrust coefficients, is modelled using Newton's second law of motion. The force and moment equations were obtained, and they were then converted into matrix and state equation form, together with the transformation matrices. The essential equations with six degrees of freedom (6 DoF) and 12 state matrices including the control input and manipulating variables were obtained. The proposed model predictive controller (MPC) was designed using the optimal model predictive controller design parameters, such as a sampling time of 0.1, a prediction horizon of 15, a control horizon of 3 and additional controller settings. With a settling period of 3 seconds, an overshoot of 0.5865, and a steady state inaccuracy of 0.00785, the MATLAB simulation demonstrates that the system variables, including roll, pitch, and yaw, are stabilized. This MPC control is more effective in anticipating and optimizing the UAV than other control strategies. Eventually, the controller's simulation on MATLAB Simulink demonstrates the controller's ability to stabilize and control the system in a real-time application. Autonomous vertical takeoff and landing operations depend heavily on the mathematical model and architecture of the flight controller. Among the uses are inspection, monitoring, and rescue.

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Section: Linear Responsesmentioning

confidence: 84%

Section: Validation With Previous Workmentioning

confidence: 99%

Aerodynamic modeling and performance analysis of model predictive controller for fixed wing vertical takeoff and landing unmanned aerial vehicle

Getachew,

Zeleke

2024

Eng. Res. Express

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Design and Analysis of a Small-Scale Solar Powered UAV

Anılır,

Afzal,

Al Abri

et al. 2023

Proceedings of the First International Conference on Aeronautical Sciences, Engineering and Technology

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Distributed Robust Formation Control of Heterogeneous Multi-UAVs With Disturbance Rejection

Imran,

Kurtulus,

Memon

et al. 2024

IEEE Access

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This paper investigates the formation control of multiple heterogeneous quadrotor unmanned aerial vehicles (UAVs). The research focuses on developing a distributed robust formation control strategy to effectively manage the translational and attitude motions of the UAVs utilizing an active virtual leader. The communication of each agent in a connected environment is represented by a directed graph. To align with real applications, only a minimum of one agent is required to connect with the leader. The challenge associated with controlling systems is more complicated by the inherent heterogeneity of UAVs, characterized by variations in their model parameters and the presence of external disturbances in the system dynamics. A robust term is proposed to handle time-varying disturbances added to the closed-loop systems. A comprehensive mathematical proof and numerical illustrations are provided to validate the efficacy of the proposed formation control strategy.INDEX TERMS quadrotor, unmanned aerial vehicles, distributed robust control, formation control, external disturbances.

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Extended Discrete-Time Quasi-Sliding Mode Control for VTOL UAV in the Presence of Uncertain Disturbances

Cited by 4 publications

References 38 publications

Aerodynamic modeling and performance analysis of model predictive controller for fixed wing vertical takeoff and landing unmanned aerial vehicle

Aerodynamic modeling and performance analysis of model predictive controller for fixed wing vertical takeoff and landing unmanned aerial vehicle

Design and Analysis of a Small-Scale Solar Powered UAV

Distributed Robust Formation Control of Heterogeneous Multi-UAVs With Disturbance Rejection

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