Data-Driven Koopman Controller Synthesis Based on the Extended H2 Norm Characterization
Abstract
This paper presents a new data-driven controller synthesis based on the Koopman operator and the extended H2 norm characterization of discrete-time linear systems. We model dynamical systems as polytope sets which are derived from multiple data-driven linear models obtained by the finite approximation of the Koopman operator and then used to design robust feedback controllers combined with the H2 norm characterization. The use of the H2 norm characterization is aimed to deal with the model uncertainty that arises due to the nature of the data-driven setting of the problem. The effectiveness of the proposed controller synthesis is investigated through numerical simulations.
0