Algorithm Results

This novel iterative method for optimal control of nonlinear systems is an exciting possibility for steering complex systems in situations where a linearization of those systems will not work. However, the high time complexity of the algorithm makes it questionable whether it could work in real time. The algorithm could be best implemented as an open-loop controller, sacrificing robustness for speed. In addition, re-implementing the algorithm in a lower-level language than MATLAB’s symbolic interpreter could reduce computation time.

Hardware Results

The hardware assembly of two different drone designs can serve as reference for future E-VTOL drone designs. In addition, new features tested and assembled such as Airlink, an alternative for flight with longer distance, and airspeed sensor, for advanced position tuning. With a data collection process that can be repeated in the future for better PID tuning, we now can better evaluate the tracking performance of any drone and improve the PID tuning process to better control the drone.

Simulation Results

The designed model of E-VOTL in the SOLIDWORK can be modified for future study to adopt requirements for the drone. Also, it allows us to test the physical behaviors of E-VOTL drones such as kinematics, dynamics, stress, deflection, vibration, and fluid flow. For the Gazebo simulator, the basic flight model for E-VOTL is implemented and the simulation environment for Qgroundcontroller and Gazebo is constructed. For future study, the framework can be directly used to test different flight controllers of nonlinear systems. Any designed controller system from MATLAB can be converted into a C++ script and tested in the Gazebo simulator.