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

doi:10.1117/12.2561097

13 December 2020 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

Author Affiliations +

Proceedings Volume 11448, Adaptive Optics Systems VII; 114482A (2020) https://doi.org/10.1117/12.2561097
Event: SPIE Astronomical Telescopes + Instrumentation, 2020, Online Only

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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.

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María Coronel, Nicolás Soto, Rodrigo Carvajal, Pedro Escárate, and Juan C. Agüero "Identification and model predictive control of an experimental adaptive optics setup utilizing Kautz basis functions", Proc. SPIE 11448, Adaptive Optics Systems VII, 114482A (13 December 2020); https://doi.org/10.1117/12.2561097

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