Implementation of an artificial neural network for the position control of a seesaw driven with a thrust propeller in open loop

Abstract

This project details the implementation of an artificial neural network (ANN) as the principal element of a system engineered to identify and predict future control states of a thrust-propelled seesaw in an open-loop configuration. The primary objective was to maintain the seesaw in a balanced 90° position. The system’s dynamic behaviour was analysed under minimal external disturbances, facilitating development and evaluation in a controlled environment. Experimental data were captured via a programmable Arduino UNO board transmitting over the serial port and recorded in an Excel file for subsequent processing. A Kalman filter was applied to refine the data, from which a random subset was selected to train the neural network. A comprehensive analysis of the results is presented herein, demonstrating the ANN’s satisfactory performance in the control task.