Our research is devoted to the fundamental mathematical aspects of systems theory and controller design of complex networked systems. Particular emphasis is laid on modeling uncertainties, the mismatch between a mathematical model and the real system. We develop optimization-based algorithms for the systematic design of robust or self-adapting controllers.
- Convex Optimization in Systems Theory
Linear matrix inequalities, semi-definite programming
- Robust and Multi-Objective Control
Integral Quadratic Constraints (IQCs), model uncertainties
- Analysis and Synthesis of LPV controllers
Parameter-varying systems, gain-scheduling, learning control
- Robust Optimization and Convex Relaxations
Sum-of-squares, moment relaxations
- Structured Controller Synthesis
- Analysis and Synthesis for Switched Systems
- Applications: Mechatronics and Flight-Control
SimTech Success Stories in Mathematical Systems Theory
Cluster of Excellence Data-Integrated Simulation Science (SimTech) - Project network 4
Project network 4: Data-integrated control systems design with guarantees
This project network will develop novel methods to control individual systems or networks of systems. It will exploit the benefit of data and learning strategies on top of classical first-principles models while still providing rigorous guarantees for the overall system behavior in all steps of the systems and control design cycle.