Tutorial: Implementando Controladores Preditivos N\~ao Lineares atrav\'es do Ferramental LPV

Recent works have demonstrated how Linear Parameter Varying Model Predictive Control (LPV MPC) algorithms are able to control nonlinear systems with precision and reduced computational load. Specifically, these schemes achieve comparable performances to state-of-the-art nonlinear MPCs, while requiring the solution of only one quadratic programming problem (thus being real-time capable). In this tutorial paper, we provide a step-by-step overview of how to implement such LPV MPC algorithms, covering from modelling to stability aspects. For illustration purposes, we consider a realistic implementation for a gas-lift petroleoum extraction process, comparing the LPV approach with the becnhmark nonlinear MPC software CasADi.
Comment: Main text in portuguese, submitted to the 2023 Simp\'osio Brasileiro de Automa\c{c}\~ao Inteligente (SBAI 2023)