ORCID Identifier(s)


Graduation Semester and Year




Document Type


Degree Name

Master of Science in Aerospace Engineering


Mechanical and Aerospace Engineering

First Advisor

Kamesh Subbarao

Second Advisor

Atilla Dogan


Attempts to completely remove the tails from aircraft can be dated back to the early days of modern aviation. A number of stability and control problems arising from the unique characteristics of the configuration resulted in poor handling qualities and some dangerous flight characteristics in the early designs. Lately, this configuration is becoming widespread again and the current state-of-the-art of fly-by wire technology and modern control design techniques enable design of tailless aircraft which are safe to fly. In this thesis, a study on the application of modern robust control design techniques on a tailless UAV is presented. A nonlinear mathematical model for the aircraft is constructed and control laws are synthesized using mu-synthesis approach. Three different scheduling methods are investigated for the control laws: ad-hoc linear interpolation, synthesis using simplified linear parameter varying models and stability preserving interpolation. A control allocation module is implemented to distribute the controller commands into highly coupled control effectors in real time. Two different allocation approaches are investigated: Cascaded Generalized Inverses and Weighted Least Squares. Effector limits and failure conditions are taken into account in an efficient way in allocation. A simulation study is performed using the nonlinear aircraft model, control laws, and control allocation models for various maneuvers and control effector failure cases.


Unmanned aerial vehicles, Tailless UAV, Control allocation, Mu-synthesis, Controller scheduling, Synthesis using simplified LPV models, Stability preserving interpolation, Cascaded generalized inverses, Weighted Least Squares


Aerospace Engineering | Engineering | Mechanical Engineering


Degree granted by The University of Texas at Arlington