Observadores No Lineales
Jaime Alberto Moreno Pérez
Martes 14 de octubre, 2014
09:00 -- 12:00 & 14:00 – 17:00
Tulum 1, MaM-1
Resumen: Observing a dynamical system consists in estimating unmeasured (internal) variables from the information obtained from the measurements and the knowledge of the model. Observation is one of the basic problems in control, and it has been studied during the last half century. It finds application in Output Feedback Control, Fault Detection and Isolation, Supervision, Fault Tolerant Control, Adaptive Control, Software Sensors, … Understanding the basic features of observers, such as convergence velocity, noise sensitivity, and robustness against model uncertainty and perturbations, is crucial for a successful application. Although for linear systems their characteristics are well understood and there are powerful design algorithms, they offer very challenging problems for nonlinear and other classes of systems.
The objective of this course, divided in 6 lectures, is to give an overview of this vast topic, ranging from the basic linear theory, passing through the ubiquitous Extended Kalman Filter and culminating with a description of several methods of observer design for nonlinear systems. The mathematical developments are complemented by examples taken from different fields. Their behavior in closed loop, under sensor noise and their robustness under model uncertainties and perturbations is also discussed.
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