Model Predictive Control for Micro Aerial Vehicle Systems (MAV) Systems
This addresses trajectory tracking for micro aerial vehicles, but it appears incremental as it builds on existing MPC and guidance methods.
The paper tackles real-time path-following for quadcopter trajectories by using Non-Linear Guidance Logic and solving convex optimization problems with feasibility constraints, resulting in the design and implementation of explicit MPC controllers executed on a computer to control hovering flight.
This paper presents a method for path-following for quadcopter trajectories in real time. Non-Linear Guidance Logic is used to find the intercepts of the subsequent destination. Trajectory tracking is implemented by formulating the trajectory of the quadcopter using its jerk, in discrete time, and then solving a convex optimization problem on each decoupled axis. Based on the maximum possible thrust and angular rates of the quadcopter, feasibility constraints for the quadcopter have been derived. In this report we describe the design and implementation of explicit MPC controllers where the controllers were executed on a computer using sparse solvers to control the vehicle in hovering flight.