O
Oliver Sawodny
Researcher at University of Stuttgart
Publications - 644
Citations - 7417
Oliver Sawodny is an academic researcher from University of Stuttgart. The author has contributed to research in topics: Feed forward & Control theory. The author has an hindex of 34, co-authored 594 publications receiving 5895 citations. Previous affiliations of Oliver Sawodny include Audi & Technische Universität Ilmenau.
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Modellbildung, Identifikation und Simulation in der Automatisierungstechnik
TL;DR: In dieser Sonderausgabe der at Automatisierungstechnik diese nun einer breiten Leserschaft zuganglich gemacht werden, dass analytische Methoden auch im industriellen Kontext zu neuen Funktionalitaten fuhren konnen.
Proceedings ArticleDOI
OVMS-plus at the LBT: disturbance compensation simplified
Michael C. Böhm,Jörg-Uwe Pott,J. Borelli,Phil Hinz,Denis Defrere,E. Downey,John M. Hill,K. Summers,Al Conrad,Martin Kürster,Tom Herbst,Oliver Sawodny +11 more
TL;DR: In this article, the authors revisited the optical vibration measurement system (OVMS) at the Large Binocular Telescope (LBT) and how these values are used for disturbance compensation.
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Modeling of a Permanent Magnet Synchronous Motor of an E-Scooter for Simulation with Battery Aging Model
TL;DR: In this article, an implementation of a time efficient powertrain model consisting of an electric motor, power electronics and a Li-ion battery with aging prediction is presented, which provides a possibility to evaluate the longterm cell aging behavior under realistic drive cycles taking motor effects into account.
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Modeling and Boundary Control of a Hanging Cable Immersed in Water
TL;DR: In this paper, a nonlinear distributed parameter system model governing the motion of a cable with an attached payload immersed in water is derived, and a two degree of freedom controller is designed for this system with a Dirichlet input at the boundary opposite to the payload.
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Robust Fault Diagnosis for Adaptive Structures With Unknown Stochastic Disturbances
TL;DR: This article combines the model- based method of parity equation with the data-based method of principal component analysis (PCA) for the fault diagnosis in adaptive structures and characterizes the unknown disturbance in the residual data derived by parity equations using PCA.