(untitled) (Revista Interdisciplinar de Pesquisa em Engenharia, 2017)
This paper describes and analyzes the performance of two different formulations ofÂ model predictive control (MPC) applied to a quadrotor unmanned aerial vehicle (UAV), one thatÂ explicitly handles constraints and another that doesn’t. The objective of the MPC strategy is toÂ compute an optimal sequence of actions within its prediction horizon to track desired states. TheÂ optimization strategies adopted in this work are based on an approximated dynamical modelÂ for prediction while imposing a quadratic cost function. One prominent vantage of MPC is itsÂ ability to handle constraints inherent to the process, based either on actuators’ limitations orÂ security concerns. Through simulations, the impacts of imposing a convex set of constraints isÂ analyzed, regarding the performance and computational effort involved in solving a trajectoryÂ tracking problem. Keywords: Optimal control, Predictive Control, Quadrotors, UAVs