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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS)
Baba Mohammed
University Tahri Mohammed Bechar
Control & Systems Engineering Electrical & Electronics Engineering

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Feedforward neural network emulation of a PID continuous-time controller for quadcopter attitude digital control Baba Mohammed; Bennaceur Said; Bounaama Fateh
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 14, No 2: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v14.i2.pp799-808

Abstract

Quadcopters are popular UAVs owing to their compact size and maneuverability. Quadcopters are unmanned aircraft guided by remote control, and the demand for them is increasing due to their widespread surveillance, goods delivery, aerial photography, and defense applications. Nonlinear quadcopter operation makes control system implementation very challenging. In this paper, based on artificial intelligence (AI), we train a feedforward neural network (FFNN) controller of a traditional proportional integral derivative (PID). The conventional (PID) is generally tuned to improve the quadcopter control and performance. FFNN can perform offline learning between the inputs and outputs of the controller to learn its behavior. Once the learning is complete, we replace the PID controller with the neural network controller, to get a controller that can maintain system stability,and overcome the limitations of hardware implementation problems caused by the classical PID controller.
Co-Authors Bennaceur Said Bounaama Fateh