Design and optimization of backstepping controller for an underactuated autonomous quadrotor unmanned aerial vehicle

Abstract

The development of a high performance controller for a quadrotor unmanned aerial vehicle (UAV) is a challenging issue since a quadrotor is an underactuated and a highly unstable nonlinear system. In this paper, the contribution is focused on the design and optimization of a controller for an autonomous quadrotor UAV. Firstly, the dynamic model of the aerial vehicle is mathematically formulated. Then, an optimal backstepping controller (OBC) is proposed. Conventionally, control parameters of a backstepping controller (BC) are often chosen arbitrarily. To this end, it is necessary to invoke a well-established optimization algorithm in order to find the best parameters. Here, the particle swarm optimization (PSO) is utilized as a new key idea to determine the optimal values of the BC parameters. In the algorithm, the control parameters are computed by minimizing the fitness function defined by using the integral absolute error (IAE) performance index. Since the control law is derived based on the Lyapunov theorem, the asymptotical stability of the system can be guaranteed. Finally, the efficiency of the proposed OBC is illustrated by implementing several simulation experiments