Author

Han Woong Bae

Date of Award

2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Mechanical and Aerospace Engineering

Committee Chair

Farbod Fahimi

Committee Member

Yuri Shtessel

Committee Member

Mark Lin

Committee Member

Chang-kwon Kang

Committee Member

Konstantinos Kanistras

Subject(s)

Quadrotor helicopters., Nonlinear control theory., Sliding mode control., Reinforcement learning., MIMO systems.

Abstract

In this dissertation, two robust single loop nonlinear controllers are proposed for an underactuated quadrotor: a sliding mode controller and an online reinforcement learning controller. The proposed controllers control the position of the control point, a displaced point from the quadrotor's geometric center, and the yaw angle. This method solves singularity issues in control matrix inversion and enables the utilization of the multi-input multi-output equation to derive the control laws. In the proposed approach, roll and pitch are not directly controlled. However, auxiliary terms are developed and utilized in both controllers to actively stabilize the roll and pitch of the quadrotor. With the aid of a unique design of sliding surface in the sliding mode control and a control mixer in the online reinforcement learning control, a single loop nonlinear control for trajectory tracking problem is achieved. The effectiveness of proposed sliding mode control is shown with simulation and experimental results in the tracking of a trajectory under parametric uncertainties. The simulation results show that the proposed online reinforcement learning controller is simultaneously robust against all three of the following: external wind disturbance, parametric uncertainties, and actuator faults.

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