Real-Time Adaptive Intelligent Control System for Quadcopter Unmanned Aerial Vehicles With Payload Uncertainties

Muthusamy, P.; Garratt, Matthew A.; Pota, H. R.; Muthusamy, Rajkumar

doi:10.1109/tie.2021.3055170

Cited by 48 publications

(23 citation statements)

References 31 publications

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“…We consider the altitude subsystem because in quadrotor mode, the weight of the biplane is balanced by the thrust. By using (10) but for an uncertain mass m * , the altitude subsystem is written as…”

Section: Adaptive Backstepping Controller Designmentioning

confidence: 99%

“…Mofid et al address a sensor failure scenario in UAVs by considering a PID-SMC (Sliding mode control) technique when the upper bound of disturbance is known, and an adaptive PID-SMC maintains desired position when the disturbance bound is unknown [9]. Muthusamy et al propose a novel bidirectional fuzzy brain emotional learning controller for a quadcopter's trajectory tracking while handling payload uncertainties in real-time [10]. Backstepping method helps control longitudinal and lateral-directional motions for miniature UAV autopilots for desirable controller performance despite model parametric uncertainties or disturbances [11].…”

Section: Introductionmentioning

confidence: 99%

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Adaptive backstepping controller design of quadrotor biplane for payload delivery

Dalwadi

Deb

Muyeen

2022

IET Intelligent Trans Sys

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Performance of the UAVs for a particular application can be enhanced by hybrid design, where take-off, hover, and landing happen like rotary-wing UAVs, and flies like fixed-wing UAVs. A backstepping controller and an adaptive backstepping controller are designed for trajectory tracking and payload delivery in a medical emergency or medical substance delivery like vaccine delivery in the presence of wind gust. Simulation results show that the backstepping controller effectively tracks the trajectory during the entire flight envelope, including take-off, hovering, the transition phase, level flight mode, and landing. A comparison between Backstepping, Integral Terminal Sliding Mode (ITSMC) and Adaptive Backstepping controllers for payload delivery show that the adaptive backstepping controller effectively tracks the altitude and attitude. ITSMC is capable of tracking the desired trajectory for a change in the mass but has sluggish response. The backstepping controller generates a steady-state error in altitude during the mass change in biplane quadrotor.

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Section: Adaptive Backstepping Controller Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive backstepping controller design of quadrotor biplane for payload delivery

Dalwadi

Deb

Muyeen

2022

IET Intelligent Trans Sys

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“…Adaptive control theory is one of the many fields explored by scientists. Among the techniques applied in this field, neural networks (NNs) are the fastest-growing group-they find use in robotics [1], optimization of complex control schemes, e.g., predictive control [2], or combinations with other intelligent structures such as fuzzy systems [3]. They ensure a model-free design process and recalculation of internal coefficients under changes of the operating point.…”

Section: Introductionmentioning

confidence: 99%

Grey Wolf Optimizer in Design Process of the Recurrent Wavelet Neural Controller Applied for Two-Mass System

2022

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In this paper, an adaptive speed controller of the electrical drive is presented. The main part of the control structure is based on the Recurrent Wavelet Neural Network (RWNN). The mechanical part of the plant is considered as an elastic connection of two DC machines. Oscillation damping and robustness against parameter changes are achieved using network parameters updates (online). Moreover, the various combinations of the feedbacks from the state variables are considered. The initial weights of the neural network and the additional gains are tuned using a modified version of the Grey Wolf Optimizer. Convergence of the calculation is forced using a new definition. For theoretical analysis, numerical tests are presented. Then, the RWNN is implemented in a dSPACE card. Finally, the simulation results are verified experimentally.

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“…In [12], a cooperative path following control is given to improve the stability of the quadcopter with unknown external disturbances. In [13], a bidirectional fuzzy brain emotional learning controller is proposed to solve the problem of the payload uncertainties and disturbances. In [14], a robust control with a disturbance observer is considered to improve the stability of the quadcopter.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Stiffness Enhancement of the Quadcopter Control System

Yao¹,

Lin²

2022

Electronics

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Vibrations often result in fatigue breakage in quadcopter flight operations. Reducing the vibration effect is the main important issue for quadcopter flight. Enhanced dynamic stiffness is required in the quadcopter control system for the vibration rejection ability. In this paper, the dynamic stiffness of the quadcopter control system is constructed and is used as an index for the performance of the quadcopter control system to resist an external oscillatory load. To rapidly reduce the vibration effect, a repetitive controller is introduced in the quadcopter control system, where the direct dynamic stiffness and the quadrature dynamic stiffness with variable frequencies are proposed. A theoretical model of the dynamic stiffness of the quadcopter control system is established by analyzing the definition of dynamic stiffness. Simulated and experimental results show that the magnitudes of the direct dynamic stiffness with the proposed repetitive controller are larger than those without the repetitive controller. The quadrature dynamic stiffness with the proposed repetitive controller is relatively smooth compared to that without the proposed repetitive controller, which can be used to verify the stability being improved by the designed repetitive controller. In addition, the magnitudes of the loss factor of the quadcopter control system with the repetitive controller are lower than those without the repetitive controller.

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Real-Time Adaptive Intelligent Control System for Quadcopter Unmanned Aerial Vehicles With Payload Uncertainties

Cited by 48 publications

References 31 publications

Adaptive backstepping controller design of quadrotor biplane for payload delivery

Adaptive backstepping controller design of quadrotor biplane for payload delivery

Grey Wolf Optimizer in Design Process of the Recurrent Wavelet Neural Controller Applied for Two-Mass System

Dynamic Stiffness Enhancement of the Quadcopter Control System

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