Model Predictive Control for Multi-Rotor Aerial Vehicle

Abstract

Model Predictive Control (MPC) is a model-based optimization-based predictive control method which has gained large popularity in its early days in the process and chemical industries. More recently, thanks to the growing availability of efficient and more computationally powerful embedded computers, the popularity of MPC is broadening to safety and time-critical applications with fast dynamics, e.g., in the automotive and robotic fields. MPC popularity is mainly due to 1) its ability to optimize, in a predictive fashion, the system behaviour on a given future time horizon based on the system model; 2) it allows to enforce dynamic constraints on the state and the control inputs of a physical system; 3) it uses states feedback to mitigate possible model perturbations.

In this lecture, we will introduce MPC and especially Nonlinear MPC. After that we will develop a mathematical model for Multi-Rotor Aerial Vehicles (MRAVs), and then we will introduce practical use-cases for MPC to control MRAVs.

This workshop and visit were part of the Horizon-Europe AeroSTREAM project.