Romeo Ortega: Parameter Estimation and Gradient: Descent-based Observers: Application to Electromechanical and Reaction Systems

On June 17, Romeo Ortega ( DR CNRS, LSS in Paris will give a seminar at LAGEPP in Bordet room.
That’s information about this presentation.

Abstract: In the first part of the talk we present a new approach to state observation, called Parameter
Estimation-based Observers (PEBO) whose main idea is to translate the state estimation
problem into one of estimation of constant, unknown parameters. The class of systems for
which is applicable is identified via two assumptions related to the transformability of the
system into a suitable cascaded form and our ability to estimate the unknown parameters.
The first condition involves the solvability of a partial differential equation while the second
one requires some persistency of excitation–like conditions. We present also PEBO in a
unified framework together with the—by-now classical—Kasantzis-Kravaris-Luenberger and
Immersion and Invariance observers.
In the second part we show that, for systems for which a linear regression-like relation is
available, it is possible to combine PEBO with a new estimation technique called Dynamic
Regressor Extension (DREM). This new technique, called DREMBAO, is used to generate
adaptive observers. PEBO and DREMBAO are shown to be applicable to position estimation
of a class of electromechanical systems, for the reconstruction of the state of power
converters, for speed observation of a class of mechanical systems and for state observation
of chemical/bio-chemical reaction systems.
The performance of these observers is compared in two physical examples with high-gain
and sliding mode observers. As expected, it is shown that—in the presence of noise—the
performance of the two latter designs is significantly below par with respect to the other

Date(s) - 17 Jun 2019
14 h 00 min - 16 h 00 min

LAGEPP Salle Jacques Bordet


Filed under: Seminaries