17/06/2019, Seminar of Romeo Ortega

Date de publication : May 29, 2019 7:39:57 AM

Date: 17/06/2019, 14h00

Location: Salle Jacques Bordet (LAGEPP)

Speaker: Romeo Ortega, L2S Supelec

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

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 techniques.