Professor

Sina Ober-Blobaum

Associate Professor of Engineering Science

Fellow of Harris Manchester College

TEL: 01865 273153
COLLEGE: Harris Manchester College
  • Biography
  • Research
  • Publications

Biography

Sina Ober-Blöbaum is an Associate Professor of Control Engineering and a Tutorial Fellow in Engineering at Harris Manchester College.

Her research is situated in the fields of Nonlinear Dynamical Systems, Numerical Integration and Optimal Control. Her research focus lies in the development and analysis of structure-preserving simulation and optimal control methods for mechanical, electrical and hybrid systems, with a wide range of application areas including astrodynamics, drive technology and robotics.

Prior to Oxford, Sina was an Assistant Professor of Computational Dynamics and Optimal Control at the Institute of Mathematics at the University of Paderborn in Germany. She was a Visiting and Deputy Professor of Applied Mathematics at the Technische Universität München, the Technische Universität Dresden and the Freie Universität Berlin in Germany.

She obtained her PhD in Applied Mathematics at the University of Paderborn and was a Postdoctoral Fellow at the Control and Dynamical Systems (CDS) group at the California Institute of Technology in Pasadena in California, USA.

Sina is a member of the International Association of Applied Mathematics and Mechanics (GAMM), an associated member of `Junges Kolleg’ of the North Rhine-Westphalian Academy of Sciences, Humanities and the Arts in Germany and associated partner of the Leading-Edge Cluster it’s OWL – Intelligent Technical Systems OstWestfalenLippe within the cross-sectional project `Self-optimisation’ . She is a frequent speaker at academic conferences on applied mathematics, computational mechanics and control engineering.

Research Interests

Structure-preserving integration

Simulations of dynamical systems are intended to reproduce the dynamic behavior in a realistic way. Using structure-preserving integration schemes for the simulation of mechanical systems, certain properties of the real system are conserved in the numerical solution. Examples are the conservation of energy or momentum induced by symmetries in the system (e. g. conservation of the angular momentum in case of rotational symmetry). A special class of structure-preserving integrators are variational integrators that are derived based on discrete variational mechanics. Using the concept of discrete variational mechanics, variational multirate integrators as well as adaptive step size strategies are developed for an efficient treatment of systems with different time scales. Moreover, the integrators are extended for the application to new system classes such as electric circuits well as for Lie-group simulations of flexible beams.


Optimal control methods

Optimal control aims to prescribe the motion of a dynamical system in such a way that a certain optimality criterion is achieved. The research focus lies in the development of efficient numerical schemes for the solution of optimal control problems that are based on structure-preserving integration. In particular, optimal control methods are designed for the treatment of multi-body systems as well as for complex systems with certain substructures for which hierarchical approaches are developed. Further aspects of research interest are the development of numerical methods using inherent properties of the dynamical system such as symmetries or invariant objects, multiobjective optimization approaches for optimal control problems and the optimal control of hybrid systems. Besides the investigation of theoretical aspects regarding accuracy and convergence of the numerical schemes, their performance is validated by means of problems from different fields of applications, e.g. mechatronic systems, biomechanics and astrodynamics.

Research Groups

Recent Projects

  • June 2017 - Present EPSRC-project Fractional Variational Integration and Optimal Control
  • 2012 - 2015 Leading-Edge Cluster 'It’s OWL' – Intelligent Technical Systems OstWestfalenLippe, crosssectional project Self-optimization
  • 2009 - 2013 German Research Foundation (DFG) research project CRC 614, A1 Self-optimizing systems in mechanical engineering: model-oriented self-optimization