Identification and model predictive control of an experimental adaptive optics setup utilizing Kautz basis functions

María Coronel, Nicolás Soto, Rodrigo Carvajal, Pedro Escárate, Juan C. Agüero

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In this paper, we develop an identification technique based on continuous-time Kautz basis functions and Maximum Likelihood estimation from discrete-time data to obtain a continuous-time model of a laboratory adaptive optics system. We illustrate the proposed identification method using synthetic data and experimental data of a laboratory adaptive optics setup. Finally we utilize the estimated model to develop a Model Predictive Control strategy that considers the deformable mirror actuation constraints. We illustrate the benefits of the model predictive control strategy via simulations and compare it against the classical Proportional-Integral controller.

Original languageEnglish
Title of host publicationAdaptive Optics Systems VII
EditorsLaura Schreiber, Dirk Schmidt, Elise Vernet
PublisherSPIE
ISBN (Electronic)9781510636835
DOIs
StatePublished - 2020
Externally publishedYes
EventAdaptive Optics Systems VII 2020 - Virtual, Online, United States
Duration: 14 Dec 202022 Dec 2020

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11448
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceAdaptive Optics Systems VII 2020
Country/TerritoryUnited States
CityVirtual, Online
Period14/12/2022/12/20

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