Altitude Control of Heavy-Lift Hexacopter using Direct Inverse Control Based on Elman Recurrent Neural Network

Abstract

This paper proposes the use of Direct Inverse Control (DIC) with Elman Recurrent Neural Network (ERNN) learning algorithm for the altitude control of a heavy-lift hexacopter. The study was conducted analytically using the real flight data obtained from real plant experiment. The results showed that the ERNN can successfully control the altitude of the heavy-lift hexacopter, where the response generated by the DIC system was in good agreement with the test data with low error. Furthermore, the proposed DIC system can also control the attitude, e.g. roll, pitch and yaw of the hexacopter which are also crucial for the hexacopter movement control.