Nonlinear Adaptive Control of Quadrotor

Abstract

In this research, nonlinear and adaptive controls of quadrotors are designed. The system is considered as an under-actuated system, which has six degrees of freedom (DOF) and four actuators. In addition, a nonlinear model is taken into account and considered to suffer from the presence of parameter uncertainty. All the plant's parameters, such as mass, system inertia, thrust and drag factors, are considered to be fully unknown and varying with time without any prior information. Firstly, a direct and an indirect model reference adaptive controls are combined to form a nonlinear composite adaptive control, which is driven using the information from both the tracking errors and the parameters' error. This controller is designed to achieve output tracking with parametric convergence. The stability of the closed-loop system is shown in the flight region of interest. Secondly, a novel switched controller using multi Lyapunov function (MLF) is proposed. This controller is designed to overcome the system's under-actuated difficulties. Practically, the system is decomposed into three fully actuated subsystems; in pitch, roll and yaw domains. Each of these subsystems targets to control only a 2-DOF. The stability of the controller is proven in region of interest with a simulation results. Finally, a combination of the MLF and the composite adaptive controller is investigated. This cooperation is proven to achieve an output tracking with a good parametric convergence. The stability of the system in the flight region of interest is proven. In addition, the performance of the proposed controller is found to follow a desired position, velocity, acceleration and the heading angle of quadrotor despite of the fully unknown parameters.