The research focus of the Trustworthy Autonomy for Smart Adaptive Systems (TASAS) group in the Institute for Systems Theory and Automatic Control (IST) is on fundamental questions pertaining modelling, analysis, and control of uncertain linear and nonlinear dynamical systems. We pursue research on both model- and data-based approaches, convinced that reconciling these two viewpoints and leveraging the respective strengths is key to achieve safety and reduce conservatism for efficient and optimal operation of complex systems. The basic research questions we explore lie at the intersection of control theory, optimization and learning and include: data-driven control theory; system identification; uncertainty quantification; optimization; robust control; dynamical systems theory.
The overarching goal of our research is to foster trustworthy autonomy by contributing to progress on the design of intelligent systems for a sustainable society, especially in the fields of energy and transportation systems and industry 4.0.
More information on specific projects and current research interests can be found on the personal pages of the group members and in the pages linked below.