Event-Triggered-Based Discrete-Time Neural Control for a Quadrotor UAV Using Disturbance Observer

An event-triggered-based (ETB) discrete-time neural control is studied for a quadrotor unmanned aerial vehicle (UAV) with external disturbances and input saturation by using the discrete-time disturbance observer (DTDO). First, the ETB mechanism of the neural network is given and the Sigmoid-type function is employed to tackle the problem of input saturation. Then, the DTDO is designed and the saturation function is utilized to ensure the boundedness of virtual control signal. Combining the discrete-time tracking differentiator and the backstepping technology, the stability of the closed-loop system is analyzed. Finally, the experiment results of the quadrotor UAV system are given to illustrate the feasibility of the proposed control scheme.