Show simple item record

dc.contributor.advisorAl Jarrah, Mohammad Amin
dc.contributor.authorAl Younes, Younes
dc.date.accessioned2011-03-10T12:43:37Z
dc.date.available2011-03-10T12:43:37Z
dc.date.issued2009-10
dc.identifier.other35.232-2009.04
dc.identifier.urihttp://hdl.handle.net/11073/131
dc.descriptionA Master of Science Thesis in Mechatronics Submitted by Younes Al Younes Entitled, "Establishing Autonomous AUS-Quadrotor," October 2009. Available are both Soft and Hard Copies of the Thesis.en_US
dc.description.abstractVertical takeoff and landing Unmanned Aerial Vehicles (VTOL-UAVs) are superior to their counterparts fixed wing UAVs for urban applications. The objective of this thesis is to establish a VTOL UAV platform to complement the ongoing research activities in the area of Autonomous cooperative multi-agent system at AUS. The chosen platform for this research is a commercial remotely controlled quadrotor. First, the mathematical model will be developed and flight simulator will be designed using Matlab/Simulink environment. The simulator will be used to develop attitude stabilization flight control laws taking into account simulated noisy inertial measurements. Then hover autopilots will be designed using classical PID and LQR controllers. These autopilots will be used to simulate basic trajectory tracking flights. These autopilots and subsequent trajectory generation and tracking will be used as a benchmark for developing nonlinear autopilots. The proposed nonlinear autopilots will be based on Adaptive Integral Backstepping Controller (AIBC) for controlling the quadrotor. The recursive Lyapunov methodology in the backstepping technique will ensure the system stability, the integral action will increase the system robustness against disturbances and model uncertainties, and the adaptation law will estimate the modeling errors caused by assumptions in simplifying the complexity of the quadrotor model. In addition, a Lyapunov-based Velocity Controller (LVC) is introduced to work side by side with the AIBC for hover and like-hover control. Fuzzy logic methodology will be investigated with the objective of boosting the performance of the AIBC by scheduling its parameters based on the state of the vehicle. Since the quadrotor is electrically powered, minimizing the control effort while keeping track of the trajectory will be investigated using least mean square algorithm. Furthermore, for path following the Tangent Heading Algorithm (THA) is proposed. To achieve the goals of this research one needs to develop in the process a Ground Control Station (GCS) for data logging, monitoring, and controlling the AUS quadrotor while performing its planned tasks. The system will be developed using hardware in the loop simulation to test and verify the development of the flight controls and the trajectory tracking ability. These simulations will validated through subsequent flight experiments.en_US
dc.description.sponsorshipCollege of Engineeringen_US
dc.description.sponsorshipMultidisciplinary Programsen_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesMaster of Science in Mechatronics Engineering (MSMTR)en_US
dc.subject.lcshVertically rising aircraften_US
dc.subject.lcshDesign and constructionen_US
dc.subject.lcshVehicles, Remotely piloteden_US
dc.subject.lcshRemote controlen_US
dc.subject.lcshDrone aircraften_US
dc.titleEstablishing Autonomous AUS-Quadrotoren_US
dc.typeThesisen_US


Files in this item

Thumbnail
Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record