A qLPV-MPC Control Strategy for Trajectory Tracking of Quadrotors
Daniel Rodriguez-Guevara, Antonio Favela‐Contreras, Oscar Julian Gonzalez Villarreal
Abstract
This article proposes a model predictive control (MPC) strategy for a quadrotor drone trajectory tracking based on a compact state-space model based on a quasi-linear parameter varying (qLPV) representation of the nonlinear quadrotor. The use of a qLPV representation allows for faster execution times, which can be suitable for real-time applications and for solving the optimization problem using quadratic programming (QP). The estimation of future values of the scheduling parameters along the prediction horizon is made by using the planned trajectory based on the previous optimal control actions. The performance of the proposed approach is tested by following different trajectories in simulation to show the effectiveness of the proposed control scheme.