An Online Adaptive Control Strategy for Trajectory Tracking of Quadrotors Based on Fuzzy Approximation and Robust Sliding Mode Algorithm

Xu, Bowen; Lü, Xiaohong

doi:10.1109/access.2020.3039546

Cited by 17 publications

(3 citation statements)

References 45 publications

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“…Zare et al [32] integrated SMC with fuzzy logic based on Lyapunov function and optimized it using an intelligent fuzzy-genetic algorithm and applied it to quadcopter slung load position and attitude control, the proposed method exhibited good stability, robustness, and tracking performance in case of transient and steady states with external disturbances, and effectively reduced the chattering phenomenon. Xu and Lu [33] integrated fuzzy control and SMC for accurate trajectory tracking of quadcopters under time-varying model uncertainties and external disturbances and proved the uniform stability of the proposed system. Abro et al [34] proposed a model-free based single-dimension fuzzy Sliding Mode Control (MFSDF-SMC) scheme for controlling attitude and position of underactuated quadcopters, and compared it with conventional SMC methods via simulation, results demonstrated that the proposed scheme exhibited robust trajectory tracking performance.…”

Section: Literature Reviewmentioning

confidence: 95%

Adaptive Neuro-Fuzzy Inference System Based on Sliding Mode Control for Quadcopter Trajectory Tracking with the Presence of External Disturbance

Darwito¹,

Indayu²

2023

JISC

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Objective of this study is to develop a novel, effective, and robust Sliding Mode Control (SMC) method for quadcopters (also called quadrotors) based on Adaptive Neuro-Fuzzy Inference System (ANFIS) for the purposes of enhancing trajectory tracking performance and realizing safe and reliable flight. In the paper, the ANFIS was combined with SMC technology to propose a scheme of adaptive robust controller, which is composed of three sub-controllers, x position controller, y position controller, and z position (altitude) controller. The proposed method can realize position tracking control of quadcopters in the presence of external disturbances. With the help of ANFIS, an adjustable gain rather than a fixed gain was established for the SMC controller, the optimal output could be attained based on a set of rules, and the position control gain was updated by ANFIS, enabling the SMC to adapt to environmental changes. Through modelling, simulation and comparison, experimental data verified that the proposed ANFIS-SMC controller outperformed conventional SMC controller in terms of convergence speed, robustness, accuracy, and stability with a maximum mean error of 0.125 meters in trajectory tracking. Research findings of this paper could contribute to the development of robust and responsive control strategies for Unmanned aerial vehicles (UAVs) trajectory tracking by providing valuable insights into the design of more effective and efficient control systems for UAVs, particularly in the context of dynamic environmental conditions.

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Section: Literature Reviewmentioning

confidence: 95%

Adaptive Neuro-Fuzzy Inference System Based on Sliding Mode Control for Quadcopter Trajectory Tracking with the Presence of External Disturbance

Darwito¹,

Indayu²

2023

JISC

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“…The design of the tracking system with Sliding Mode Controller and Fuzzy Type-2 has succeeded in tracking the required track and significantly reducing the chatter generated by the SMC. Quadcopter is divided into two subsystems, namely, attitude and position [10][11][12]. In addition to directing movement based on the trajectory, a quadcopter control system has also developed a moving target tracking system, and the research was carried out using a camera based on the Fuzzy-PI control system [13].…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of a Sliding Mode Control-Kalman Filter-Based Mathematical Model for Altitude and Attitude Control in Quadcopters

Darwito,

Agustina

2023

JISC

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This study presents an evaluation of a mathematical model designed for altitude and attitude control in quadcopters, employing Sliding Mode Control (SMC) in conjunction with the Kalman Filter algorithm. The developed mathematical model focuses on controlling the quadcopter's height along the z-axis and its attitude, encompassing roll, pitch, and yaw. Simulation results demonstrate that the quadcopter achieves stable control within a time span of 2 to 4 seconds. The designed control system has been simulated, implemented on a miniquadcopter, and tested for the occurrence of chattering events. The incorporation of the SMC-Kalman Filter control system effectively mitigates chattering, resulting in enhanced stability for the quadcopter. This work show cases the potential of the proposed mathematical model in achieving precise and stable control in quadcopters, thus expanding the applicability of such systems in various applications.

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“…In the closing few decades, the quadrotor format has to turn out to be famous for small-scale unmanned aerial automobiles or drones. The want for a plane with more maneuverability and soaring capacity has brought about an upward thrust in quadrotor research [5]. The four-rotor layout lets in quadrotor to be exceedingly easy in layout but notably reliable and maneuverable.…”

Section: Introductionmentioning

confidence: 99%

Integrated Design of Adaptive & Fuzzy Logic Control for Trajectory Tracking of 2 DOF Quadrotor

Jibril

2021

Preprint

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Accurate and precise trajectory tracking is crucial for a quadrotor to operate in disturbed environments. This paper presents a novel tracking hybrid controller for a quadrotor UAV that combines the Adaptive and Fuzzy logic controller. The Adaptive fuzzy controller is implemented to govern the behavior of two degrees of freedom quadrotor UAV. The proposed controller allows controlling the movement of UAVs to track a given trajectory in a 2D vertical plane. The Fuzzy Logic system provides an automatic adjustment of the Adaptive parameters to reduce tracking errors and improve the quality of the controller. The results showed perfect behavior for the control law to control a quadrotor trajectory tracking task. To show the effectiveness of the intelligent controller, simulation results are given to confirm the advantages of the proposed control method, compared with Fuzzy and Proportional integral derivative (PID) control methods.

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An Online Adaptive Control Strategy for Trajectory Tracking of Quadrotors Based on Fuzzy Approximation and Robust Sliding Mode Algorithm

Cited by 17 publications

References 45 publications

Adaptive Neuro-Fuzzy Inference System Based on Sliding Mode Control for Quadcopter Trajectory Tracking with the Presence of External Disturbance

Adaptive Neuro-Fuzzy Inference System Based on Sliding Mode Control for Quadcopter Trajectory Tracking with the Presence of External Disturbance

Performance Evaluation of a Sliding Mode Control-Kalman Filter-Based Mathematical Model for Altitude and Attitude Control in Quadcopters

Integrated Design of Adaptive & Fuzzy Logic Control for Trajectory Tracking of 2 DOF Quadrotor

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