Control adaptativo basado en mínima varianza y filtro de Kaiman

This paper presents a methodology for designing a minimum variance control- (MVC) and Kalman filter- (KF) based adaptive system. MVC is a technique of great interest, and it is widely used because it can reduce either energy or material consumption, or else, it can increase production performance. The Kalman filter is a recursive method that provides stochastic support for adaptive systems, showing feasibility and good results for dynamic system identification. The methodology implementation was conducted in a multiplatform integrated development environment called Qt Creator Qt 4.7-based, yielding good results when applied to the reference tracking problem. Moreover, it can be observed that the adaptive control scheme exhibits good settling times and notoriously appropriate overshoots.