Graduation Semester and Year




Document Type


Degree Name

Master of Science in Aerospace Engineering


Mechanical and Aerospace Engineering

First Advisor

Kamesh Subbarao


Unmanned Aerial Systems, although still in early development, are expected to grow in both the military and civil sectors. As part of the UAV sector, the quadrotor helicopter platform has been receiving a lot of interest from various academic and research institutions because of their simplistic design and low cost to manufacture, yet remaining a challenging platform to control. Four different controllers were derived for the trajectory generation and constrained control of a quadrotor platform. The rst approach involves the linear version of the Model Predictive Control (MPC) algorithm to solve the state constrained optimization problem. The second approach uses the State Dependent Coefficient (SDC) form to capture the system non-linearities into a pseudo-linear system matrix, which is used to derive the State Dependent Riccati Equation (SDRE) based optimal control. For the third approach, the SDC form is exploited for obtaining a nonlinear equivalent of the model predictive control. Lastly, a combination of the nonlinear MPC and SDRE optimal control algorithms is used to explore the feasibility of a near real-time nonlinear optimization technique.


Aerospace Engineering | Engineering | Mechanical Engineering


Degree granted by The University of Texas at Arlington