Dynamic modeling and displacement control for differential flatness of quadrotor UAV slung-load system

Roy, Kumud Ranjan; Waghmare, L. M.; Patre, B. M.

doi:10.1007/s40435-022-00996-4

Cited by 9 publications

(6 citation statements)

References 32 publications

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“…Without a stable system, it would be difficult to fly a quadcopter and make it follow the given trajectory [4,5]. Thus, the stability is the most important task for a successful flight [6]. To design a controller, several steps must be taken and several concepts must be understood [7].…”

Section: Introductionmentioning

confidence: 99%

Comparative Study of PID, PD, LQR, and LQR-PD Regulators for Quadrotor Stabilization and Trajectory Tracking

Djizi

Zahzouh

2023

Preprint

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Quadrotors, a type of unmanned aerial vehicle, utilize four rotors for precise lift and control, making them highly versatile for a variety of tasks, such as delivery, inspection, mapping, and monitoring. The growing importance of quadcopters is due to their ability to perform a variety of tasks, such as mapping, inspection, surveillance, and delivery. However, their design and four motors make them inherently unstable and difficult to control, which can limit their potential. To improve stability, four controllers (Proportional Derivative, Proportional Integral Derivative, Linear Quadratic Regulator, and Linear Quadratic Regulator-Proportional Derivative) were tested on a quadcopter Simulink model created with MATLAB/SIMULINK. Simulation results showed that the Linear Quadratic Regulator-Proportional Derivative controller was the most effective in terms of stabilization and speed, particularly for hovering along the x and y axes. This controller was found to be reliable and efficient, providing a smooth and fast response. Tuning these controllers can optimize the quadcopter's stability, accuracy, and speed, enabling them to perform a wider range of tasks.

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Section: Introductionmentioning

confidence: 99%

Comparative Study of PID, PD, LQR, and LQR-PD Regulators for Quadrotor Stabilization and Trajectory Tracking

Djizi

Zahzouh

2023

Preprint

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“…The input-output linearization control scheme was designed for UAV slung-load systems considering nonlinearity and underactuated issues [1]. A linear matrix inequalities-based linear parameter varying (LPV) control scheme was proposed for a UAV subject to time-varying mass, timevarying inertia, and mass flow rate [2].…”

Section: Introductionmentioning

confidence: 99%

S Trajectory Based on Sliding Mode Control for Unmanned Aerial Vehicle Slung-load System

Wang,

Lu,

Huang

2023

J. Phys.: Conf. Ser.

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For unmanned aerial vehicles (UAVs) slung-load systems, the payload of UAVs may suffer swing caused by inertia and external disturbances during the delivery process, posing a threat to system safety. Simultaneously tracking the trajectory and suppressing the payload swing is a challenging task. In this paper, a control design method is presented for trajectory tracking and swing suppression for a UAV delivery system. A feedforward design with the S-shaped trajectory is employed to suppress the payload swing, and a feedback hierarchical sliding mode control is utilized for trajectory tracking. Furthermore, stability analysis of the control system is conducted using the Lyapunov function, and simulation experiments are performed in MATLAB to validate the performance of the controller.

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“…A robust tracking control problem dealing with a quadrotor subject to system nonlinearities, coupling of inputs, aerodynamic irregularities, and external factors, such as wind, is analyzed through quantitative simulation studies in Ref. [6], focusing on position and attitude control. With tracking control and disturbance elimination of multirotor-slung load systems, Liu et al [7] examine an adaptive hierarchical sliding mode controller, employing a sliding mode disturbance observer operating such that it converges in a fixed time interval.…”

Section: Introductionmentioning

confidence: 99%

Variations in Finite-Time Multi-Surface Sliding Mode Control for Multirotor Unmanned Aerial Vehicle Payload Delivery with Pendulum Swinging Effects

Peris,

Norton,

Khoo

2023

Machines

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Multi-surface sliding mode control addresses the limitations of traditional sliding mode control by employing multiple sliding surfaces to handle uncertainties, disturbances, and nonlinearities. The design process involves developing sliding surfaces, designing switching logic, and deriving control laws for each surface. In this paper, first, a robust finite-time multi-surface sliding mode controller will be presented and its performance analyzed by applying it to a multirotor subjected to a suspended payload, modeled in the form of a single pendulum, itself defined as a spatial (3D) dynamic model. Next, an adaptive finite-time multi-surface sliding mode controller will be derived—adding a variable adaptive parameter to the existing sliding surfaces of the robust finite-time control—and applied to the same system. It will be shown that the adaptive controller, with an adaptive parameter that adjusts itself based on the present value of the multi-surface sliding mode parameter, creates an improved fast finite-time convergence by obtaining an optimal settling time and minimizing undershoot of the multirotor state vector. Empirical verification of the effectiveness of the adaptive control will be carried out by presenting the control performances against a step response. It is also shown that the control may be utilized to approximate external disturbances—represented by the pendulum—and that with the application of control, the vehicle’s motion may be stabilized and the payload swing suppressed. Lyapunov stability theory-based stability proofs for the controllers’ designs are developed, showing the asymptotic stability of the output and uniform boundedness of the errors in the system dynamics. It is verified that the multi-surface sliding mode control can account for system uncertainties—both matched and mismatched—in addition to changes in internal dynamics and disturbances to the system, where the single pendulum payload is representative of the changes in dynamics that may occur to the system. Numerical simulations and characteristics are presented to validate the performance of the controllers.

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Dynamic modeling and displacement control for differential flatness of quadrotor UAV slung-load system

Cited by 9 publications

References 32 publications

Comparative Study of PID, PD, LQR, and LQR-PD Regulators for Quadrotor Stabilization and Trajectory Tracking

Comparative Study of PID, PD, LQR, and LQR-PD Regulators for Quadrotor Stabilization and Trajectory Tracking

S Trajectory Based on Sliding Mode Control for Unmanned Aerial Vehicle Slung-load System

Variations in Finite-Time Multi-Surface Sliding Mode Control for Multirotor Unmanned Aerial Vehicle Payload Delivery with Pendulum Swinging Effects

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