Software in the loop simulation for multirotor position tracking using a linear constrained model predictive controller

Abstract

The multirotor unmanned aerial vehicles (UAVs) are experiencing a currently growing interest due to their high maneuverability, simplified mechanics and vertical takeoff and landing capability. Also for these reasons, the multirotor UAVs are suitable test-bed platforms for different position tracking control techniques. This paper solves the problem of safely controlling the position tracking of a multirotor UAV by using a linear state-space model predictive controller (MPC) formulation. The optimization is performed by replacing the original conic constraint set by a circumscribed pyramidal space that renders a linear set of inequalities on the total thrust vector. In order to improve the design eficiency of such kind of control systems, the present work uses a low-cost software-in-the-loop (SIL) simulation scheme for performance evaluation of control law for quadricopter. The scheme consists of two computers interconnected by an Ethernet network using the User Datagram Protocol (UDP). Basically, one computer runs MATLAB/Simulink while the other runs X-Plane. The control law is implemented in Simulink, whereas the vehicle dynamics as well as the flight environment are simulated in X-Plane.