Control adaptativo basado en mínima varianza y filtro de Kalman

• Published in: Tecnura Vol. 17; no. 36; p. 41
• Main Authors: Zuluaga Ríos, Carlos David, Giraldo, Eduardo
• Format: Journal Article
• Language: Portuguese; Spanish
• Published: Bogota Universidad Distrital Francisco José de Caldas, Facultad Tecnológica 01-06-2013
• Subjects: DNA fingerprints; Wildlife observation
• ISSN: 0123-921X; 2248-7638

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.