Real-time model predictive control for quadrotors

Abstract

This paper presents a solution to on-board trajectory tracking control of quadrotors. The proposed approach combines the standard hierarchical control paradigm that separates the control into low-level motor control, mid-level attitude dynamics control, and a high-level trajectory tracking with a model predictive control strategy. We use dynamic reduction of the attitude dynamics and dynamic extension of the thrust control along with feedback linearisation to obtain a linear system of McMillan degree three that models force controlled position and trajectory tracking for the quadrotor. Model predictive control is then used on the feedback equivalent system and its control outputs are transformed back into the inputs for the original system. The proposed structure leads to a low complexity model predictive control algorithm that is implemented in real-time on an embedded hardware. Experimental results on different position and trajectory tracking control are presented to illustrate the application of the derived linear system and controllers.