Simple Learning-Based Robust Trajectory Tracking Control of a 2-DOF Helicopter System

Stabilization and tracking control of Unmanned Aircraft Systems (UASs) such as helicopters in a complex environment with system uncertainties, unknown disturbances, and noise is a challenging task; therefore, to compensate for system uncertainties and unknown disturbances, this paper presents a trajectory tracking control strategy for a 2-DOF (degree of freedom) helicopter system testbed by employing a gradient descent-based simple learning control law that minimizes the cost function corresponding to desired closed-loop error dynamics of the nonlinear system under control. In addition, to ensure the stability of the closed-loop nonlinear system, further analysis is provided. The learning capability of the designed controller makes it suitable to take system uncertainties and unknown disturbances into account. The results of computer simulations and real-time experiment using the Quanser AERO helicopter are included to demonstrate the effectiveness of the designed control strategy.