Design and Simulation of a Hybrid PD-ANFIS Controller for Attitude Tracking Control of a Quadrotor UAV

Khatoon, Shahida; Nasiruddin, Ibraheem; Shahid, Mohammad

doi:10.1007/s13369-017-2586-z

Cited by 34 publications

(16 citation statements)

References 49 publications

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“…In [23], the moment of inertia J T for each motor is neglected. By neglecting drag terms, gyroscopic and coriolis-centripetal, as well as unknown disturbances, the following simplified model of attitude subsystems was adopted in [2], [3]…”

Section: Problem Formulation and Preliminaries A System Descriptions And Basic Knowledgesmentioning

confidence: 99%

“…In recent years, different control methods have been developed for the QUAV, such as PID control [2]- [5], adaptive control [6], model reference adaptive control [7], and robust actuator fault detection and Diagnosis method [8]. The recent development of adaptive control schemes for the The associate editor coordinating the review of this manuscript and approving it for publication was Maurizio Magarini .…”

Section: Introductionmentioning

confidence: 99%

“…For the position subsystem, a position constraints controller is proposed, while a prescribed performance controller is proposed for the attitude subsystem based on the decentralized control technique, which can compensate for the unknown interconnections with only local subsystem measurements. The main contributions of our proposed control scheme are summarized as follows: (1) compared with the simplified model of attitude subsystems adopted in [2], [3], [6]- [8], [21], the unknown interconnections among attitude subsystems are considered in our paper; (2) both the constant constraints for position and the prescribed performance constraints for attitude tracking errors are considered, however, only the prescribed performance constraints was presented for the position subsystem in [40]; (3) the two constrains can be achieved by guaranteeing the boundedness of the filtered tracking errors without using a complex error transformation. To validate the effectiveness of the proposed scheme, simulations on a QUAV with and without unknown interconnections among attitude subsystems are performed.…”

Section: Introductionmentioning

confidence: 99%

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Trajectory Tracking Control for a QUAV With Performance Constraints

Liu

Shi

2019

IEEE Access

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In this paper, a trajectory tracking control scheme is developed for a quadrotor unmanned aerial vehicle (QUAV) with unknown inertial moments and unknown interconnections among every attitude subsystem. In this scheme, the overall control system is decoupled into a position subsystem and an attitude subsystem. For the position subsystem, a position constraints controller is proposed, while a prescribed performance constraints controller is developed for the attitude subsystem. It is proved that all the signals in the closed-loop system are bounded and that both the position constraints and the prescribed performance constraints on attitude tracking errors can be achieved by guaranteeing the boundedness of the filtered tracking errors. The simulation results demonstrate the effectiveness of the proposed scheme.INDEX TERMS QUAV, position constraints, prescribed performance control, unknown inertial moments, unknown interconnections.

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Section: Problem Formulation and Preliminaries A System Descriptions And Basic Knowledgesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Trajectory Tracking Control for a QUAV With Performance Constraints

Liu

Shi

2019

IEEE Access

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“…Theorem 2. Given the attitude control system in equation (37) and provided that the control gains b i (i ¼ 1; 2; 3) satisfy the conditions in equation ( 47), the attitude controller in equation ( 45) could guarantee the locally exponentially stability of the controlled system and the convergence of the tracking error E h in equation (9).…”

Section: Lemma 2 An Auxiliary Function Qðtþ Is Defined As Followsmentioning

confidence: 99%

“…Substituting equations (41) to (43) and equation (45) into equation (37), the closed-loop subsystem of e h3 can be obtained…”

Section: Proof Define a Lyapunov Function As Followsmentioning

confidence: 99%

Model-free control of a quadrotor using adaptive proportional derivative-sliding mode control and robust integral of the signum of the error

Zhi

2018

International Journal of Advanced Robotic Systems

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In this article, a robust model-free trajectory tracking control strategy is developed for a quadrotor in the presence of external disturbances. The proposed strategy has an outer-inner-loop control structure. The outer loop controls the position with adaptive proportional derivative-sliding mode control and generates the desired attitude angles for the inner loop corresponding to the given position, velocity, and heading references, while the robust integral of the signum of the error method is applied to the inner loop to guarantee fast convergence of attitude angles. Asymptotic tracking of the three-dimensional trajectories is proven by the Lyapunov stability theory. The effectiveness of the proposed controller is demonstrated with the simulation results by comparing with other model-free quadrotor trajectory tracking controllers.

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Three‐dimensional dead reckoning of wall‐climbing robot based on information fusion of compound extended Kalman filter

Wei

Zhang

2022

Journal of Field Robotics

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Dead reckoning accuracy determines the operation quality of pipeline mobile robot to a certain extent. With the progress of the industry, the research on the dead reckoning system of pipeline robot is more and more in-depth, but how to improve dead reckoning accuracy is still a difficult problem for pipeline mobile robot. In this paper, to overcome the sensor defects of the traditional dead reckoning system, an error backpropagation neural network (BPNN) is introduced to compensate the sensor error caused by static drift and poor dynamic response. To reduce the interference of noise information, the covariance matching technique based on the Adaptive Neuro-Fuzzy Inference System is used to estimate the measurement noise information. And then the two are combined in the algorithm based on the extended Kalman Filter (EKF) framework for data fusion. An EKF algorithm based on adaptive neural fuzzy combined with BPNN is proposed. Finally, a complete three-dimensional dead reckoning system is established by coordinate transformation. The motion experiment of the quadruped wall-climbing robot in the pipeline proves that the proximity L of the calculated trajectory is not more than 6.00%, and the lowest is 1.07%, which effectively improves the reliability, robustness, and positioning accuracy of the dead reckoning.

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Design and Simulation of a Hybrid PD-ANFIS Controller for Attitude Tracking Control of a Quadrotor UAV

Cited by 34 publications

References 49 publications

Trajectory Tracking Control for a QUAV With Performance Constraints

Trajectory Tracking Control for a QUAV With Performance Constraints

Model-free control of a quadrotor using adaptive proportional derivative-sliding mode control and robust integral of the signum of the error

Three‐dimensional dead reckoning of wall‐climbing robot based on information fusion of compound extended Kalman filter

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