This thesis presents some existing gimbal and UAV control algorithms as well as novel algorithms developed as the extensions of the existing ones. The existing image-based visual servoing algorithms for both gimbal and UAV require the depth information to the object of interest. The depth information is not measurable when only a monocular camera is used for tracking. This thesis is the result of contemplation to the question: how can the necessity for a depth measurement be removed? A novel gimbal algorithm using adaptive control is developed and presented with simulation and hardware results. Although the estimated depth using the algorithm cannot be used as reliable depth information, the target tracking objective is met. Also, a new UAV control algorithm for target following is developed and presented with simulation results. This algorithm does not require the depth to the target or the UAV altitude to be measured because it exploits the unit vectors to the target and to the optical axis.
College and Department
Ira A. Fulton College of Engineering and Technology; Electrical and Computer Engineering
BYU ScholarsArchive Citation
Lee, Jae Hun, "Nonlinear Control Framework for Gimbal and Multirotor in Target Tracking" (2018). All Theses and Dissertations. 6775.
UAV, multirotor, gimbal, adaptive control, backstepping control, target tracking