Optimal backstepping controller for trajectory tracking of a quadrotor UAV using ant colony optimisation algorithm

Abstract

This paper concerns the design of an optimal stabiliser/tracker for the quadrotor UAV. Firstly, kinematic and dynamic equations of the aerial vehicle are yielded through Newton-Euler formalism. Then, the backstepping (BS) technique is adopted to sustain a controllable and stable behaviours of the quadrotor attitude. However, designing a high-precision flight controller essentially necessitates an optimal selection of its internal parameters. The improper configuration of these parameters can negatively influence the flight performances and sometimes leads to the instability of the quadrotor system. Ant colony optimisation algorithm (ACO) is used to configure the adopted stabilised technique, and a modified cost function is proposed to improve the response of the quadrotor system. In view to corroborate the accuracy of the suggested method, a series of numerical experiments were done and comparison with other control approaches is also given.