Real-time Nonlinear Parameter Estimation and Tracking Control of Unmanned Aerial Vehicles in Closed-Loop

Abstract

The real-time unknown parameter estimation and adaptive tracking control problem are investigated in this paper for a six degrees of freedom (6-DOF) of under-actuated quadrotor unmanned aerial vehicle (UAV). A virtual proportional derivative (PD) is designed to maintain the translational dynamics. Two adaptive schemes are developed to handle the attitude dynamics of UAV with several unknown parameters. In the beginning, a classical adaptive scheme using the certainty equivalence principle is proposed and designed. The idea is to design a controller for an ideal situation by assuming the unknown parameter was known. Then the unknown parameter is replaced by its estimation. A theoretical analysis is provided to ensure the trajectory tracking of the adaptive controller. However, an inherent drawback of this scheme is that there is no guarantee for the estimated parameters to converge to the actual values. To address this issue, a new adaptive approach is developed as the next step by adding a continuous function to the control structure. The proposed technique guarantees handling of parametric uncertainties with an appropriate design manifold. The rigorous analytical proof and numerical simulation analyses are presented to show the effectiveness of the proposed control design.