(Dr. Nader Sadegh, advisor)
"Engine Modeling, Control, and Synchronization for an Unmanned Aerial Vehicle"
The design of an engine controller for an Unmanned Aerial Vehicle (UAV) is the ultimate goal of this thesis. The UAV has two internal combustion engines that are coupled together for safety reasons and for load sharing. This coupling will allow equal power from each engine to be transferred to the propellers only if both engines are turning at the same velocity. Therefore, it is critical that the two engines be controlled in such a way that allows this equilibrium condition to exist for varying load conditions. This thesis will detail the process of modeling the engine and designing the controller. This process will include the following procedures: experimental setup, data collection, system identification, model validation, controller design, and simulations. Because of the engines' nonlinear characteristics, modern techniques such as feedforward neural networks will be utilized in the modeling and feedback control. First, a dynamic perceptron network will be trained to model the relationship between the engine speed and inputs such as throttle angle, load, etc. Next, a feedforward network will be employed as a feedback controller. This network will be trained and fine-tuned based on the model and/or experimental data. Finally, a feedback controller aimed at synchronizing the speeds of the two engines will be designed and simulated. These modern techniques will not be used blindly however; they will be compared to traditional modeling and control techniques to verify the increased complexity also results in better performance.