Schirmer, D. Althaus, A. Hüser, S. Khan, S. Schüngel, T. JACoW Publishing Geneva, Switzerland 2226-0358 978-3-95450-221-9 10.18429/JACoW-ICALEPCS2021-WEPV007 English 631-635 controls storage-ring injection synchrotron electron Contribution to a conference proceedings 2022 2022-03 https://doi.org/10.18429/JACoW-ICALEPCS2021-WEPV007 https://jacow.org/icalepcs2021/papers/wepv007.pdf In recent years, several machine learning (ML) based projects have been developed to support automated monitoring and operation of the DELTA electron storage ring facility. This includes self-regulating global and local orbit correction of the stored electron beam, betatron tune feedback as well as electron transfer rate (injection) optimization. Furthermore, the implementation for a ML-based chromaticity control is currently prepared. Some of these processes were initially simulated and then successfully transferred to real machine operation. This report provides an overview of the current status of these projects.