Attitude trajectory tracking of quadrotor UAV using super-twisting observer-based adaptive controller

The successful implementation of high-level decision algorithm on quadrotor depends on the accurate trajectory tracking performance. In this paper attitude estimation and trajectory tracking control problem of quadrotor unmanned aerial vehicle (UAV) with endogenous and exogenous disturbance are considered, where the lumped disturbance characteristic does not have a probabilistic illustration but instead the dynamics are known to have a bound. The problem is handled by developing disturbance estimator and control strategy. In order to estimate lumped disturbance precisely, a globally finite time stable extended state observer is proposed based on super-twisting algorithm. Stability analysis and observer’s parameters selection rule are discussed by using Lyapunov’s stability theory. The proposed observer strategy achieves accurate observing performance of disturbance without increasing observer’s order, and chattering effect is also reduced by applying super-twisting algorithm. Furthermore, a super-twisting sliding mode control law is proposed to guarantee the asymptotic convergence of the drone’s orientation with respect to the reference. Finally, a numerical study based on simulations is presented to analyze the performance of proposed approach.