Iterative Learning Sliding Mode Control for UAV Trajectory Tracking

This paper presents a novel iterative learning sliding mode controller (ILSMC) that can be applied to the trajectory tracking of quadrotor unmanned aerial vehicles (UAVs) subject model uncertainties and external disturbances. Here, proposed ILSMC is integrated in outer loop controlled system. The control development, conducted discrete-time domain, does not require priori information disturbance bound as with conventional SMC techniques. It only involves an equivalent term for desired dynamics closed drive system state toward surface maintain robust performance. By from previous iterations, yield very accurate performance when induced without chattering. design then attitude 3DR Solo UAV built-in PID controller. simulation results experimental validation real-time data demonstrate advantages scheme over existing