Design of an Intelligent Controller for Station Keeping, Attitude Control, and Path Tracking of a Quadrotor Using Recursive Neural Networks

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Khosravian e.; MAGHSOUDI H.

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Journal Paper

Paper Information

Journal: International Journal of Engineering Year:2019 | Volume:32 | Issue:5 (TRANSACTIONS B: Applications) Page(s): 747-758

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Information Journal Paper

Title

Design of an Intelligent Controller for Station Keeping, Attitude Control, and Path Tracking of a Quadrotor Using Recursive Neural Networks

Author(s)

Khosravian e. | MAGHSOUDI H. | Issue Writer Certificate

Keywords

Artificial Neural Network

Intelligent Controlling

Non-Linear PID Control

Quadrotor

Station Keeping

Trajectory Tracking

Abstract

During recent years there has been growing interest in unmanned aerial vehicles (UAVs). Moreover, the necessity to control and navigate these vehicles has attracted much attention from researchers in this field. This is most ly due to the fact that the interactions between turbulent airflows apply complex aerodynamic forces to the system. Since the dynamics of a Quadrotor are non-linear and the system is a mult ivariable one, moreover, it has six degrees of freedom for only four control inputs, then it is an under actuated system. This is why conventional control algorithms employed to t rack desired t rajectories of fully actuated aerial vehicles are no longer applicable for Quadrotors. The main step in the manufacturing of a fully autonomous unmanned aerial vehicle is to design a controller which stabilizes the aerial vehicle in the presence of uncertainties and disturbances, then navigate it along a desired t rajectory. The aim of this study is to design and implement an intelligent controller for Station Keeping, attitude control, and path t racking of a Quadrotor. For this purpose, an Artificial Neural Network method was employed. The art ificial neural network is one of the most powerful and useful tools in the modification of a control system. In this study, the control methods conventionally applied to Quadrotors are reviewed at first. Then, in order to analyze the behavior of the system and also to design the controller, the state equations of a Quadrotor are discussed. Following that, the design of a recurrent neural network based Non-Linear PID Control algorithm is presented. Finally, the results of the simulation performed are presented, and the performance of the proposed algorithm are investigated. It was shown that by using the proposed algorithm, the Quadrotor t racks the desired t rajectory, and simultaneously, its at t itude is stabilized.

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APA: Copy

Khosravian, e., & MAGHSOUDI, H.. (2019). Design of an Intelligent Controller for Station Keeping, Attitude Control, and Path Tracking of a Quadrotor Using Recursive Neural Networks. INTERNATIONAL JOURNAL OF ENGINEERING, 32(5 (TRANSACTIONS B: Applications)), 747-758. SID. https://sid.ir/paper/722004/en

Vancouver: Copy

Khosravian e., MAGHSOUDI H.. Design of an Intelligent Controller for Station Keeping, Attitude Control, and Path Tracking of a Quadrotor Using Recursive Neural Networks. INTERNATIONAL JOURNAL OF ENGINEERING[Internet]. 2019;32(5 (TRANSACTIONS B: Applications)):747-758. Available from: https://sid.ir/paper/722004/en

IEEE: Copy

e. Khosravian, and H. MAGHSOUDI, “Design of an Intelligent Controller for Station Keeping, Attitude Control, and Path Tracking of a Quadrotor Using Recursive Neural Networks,” INTERNATIONAL JOURNAL OF ENGINEERING, vol. 32, no. 5 (TRANSACTIONS B: Applications), pp. 747–758, 2019, [Online]. Available: https://sid.ir/paper/722004/en

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