  This paper describes dynamic system identification, and full control of a
cost-effective vertical take-off and landing (VTOL) multi-rotor micro-aerial
vehicle (MAV) --- DJI Matrice 100. The dynamics of the vehicle and autopilot
controllers are identified using only a built-in IMU and utilized to design a
subsequent model predictive controller (MPC). Experimental results for the
control performance are evaluated using a motion capture system while
performing hover, step responses, and trajectory following tasks in the present
of external wind disturbances. We achieve root-mean-square (RMS) errors between
the reference and actual trajectory of x=0.021m, y=0.016m, z=0.029m,
roll=0.392deg, pitch=0.618deg, and yaw=1.087deg while performing hover. This
paper also conveys the insights we have gained about the platform and returned
to the community through open-source code, and documentation.
