Recent advances in technology have allowed for Small Unmanned Aerial Vehicles (SUAVs) to employ miniaturized smart payloads such as gimbaled cameras, deployable mechanisms, and network sensors. Gimbaled video camera systems, designed at NPS, use two servo actuators to command line of sight orientation via serial controller while tracking a target and is termed Visual Based Target Tracking (VBTT). Several Tactical Network Topology (TNT) experiments have shown high value of this new payload but also revealed inherent delays that exist between command and actuation of the pan-tilt servo actuators controlling the camera. Preliminary analysis shows that these delays are due to a communication lag between the ground control station and the onboard serial controller, a data processing delay within that controller, and the mechanical delays of the gimbal. This thesis applies system identification techniques to the servo controller system and considers the implementation of a Smith Predictor into the camera control algorithm in order to reduce the overall effect of the lag on the system performance.


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