Annika Junker, Keno Pape, Julia Timmermann
Nov 17, 2022
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IFAC-PapersOnLine
Abstract
: We present a method for designing a data-driven Koopman-operator-based model that adapts itself during operation and can be straightforwardly used for the controller and observer design. The recursive model is able to accurately describe different regions of the state space and additionally consider the occurrence of unpredictable system changes during operation. Furthermore, we show that this adaptive model is applicable to state-space control, which requires complete knowledge of the state vector. For changing system dynamics, the state observer therefore also needs to have the ability to adapt. To the best of our knowledge, there have been no approaches presently available that holistically use an adaptive Koopman-based plant model for the design of a state-space controller and observer. We demonstrate our method on a test rig: the controller and the observer adequately adapt during operation so that outstanding control performance is achieved even in the presence of strong systems changes that occur.