Seiler, Peter

Peter works in the area of robust control theory which focuses on the impact of model uncertainty on systems design. He is a contributor to the Robust Control Toolbox in Matlab. He is currently developing theoretical and numerical algorithms to assess the robustness of systems on finite time horizons. He is also investigating the use of robust control techniques to better understand optimization algorithms and model-free reinforcement learning methods.

He joined Michigan in 2020 from the University of Minnesota, where he had been working on advanced control techniques for wind turbines, fault-detection methods for safety-critical systems and robust control of disk drives.