AUTHOREN: Rolf Findeisen, Pablo Zometa and Markus Kögel

Abstract:

By now predictive control for the task of stabilization is well understood. Many schemes to guarantee stability and recursive feasibility are well known. In the frame of this talk we will focus on the application of predictive control to mechatronic and embedded systems. In the first part we propose an efficient predictive control scheme for path following with stability guarantees. The second part focuses on the fast solution of predictive control problems on embedded systems via code generation taking aspects such as stability, real-time feasibility and limited computational hardware into account. The presented results are verified considering the control of an industrial light weight robot. The talk is concluded presenting methods for cooperative and decentralized predictive control approaches.

Bio:

Rolf Findeisen is the head of the systems theory and automatic control laboratory at the Otto-von-Guericke-University Magdeburg Germany. He studied Engineering Cybernetics at the University of Stuttgart (Diploma 97), Chemical Engineering at the University of Wisconsin-Madison (M.Sc. ´97), and Information Technology at the ETH Zürch-Switzerland. In ´04 he obtained a Dr.-Ing. from the University of Stuttgart. Since ´07 he is Professor at the Otto-von-Guericke Universität Magdeburg. He hold several visiting positions, including MIT Cambridge, EPLF Lausanne, NTNU Norway and Imperial College London. He is a member of the board of governors of the state funded excellence initiative Complex Dynamical Systems, of the International Max-Planck Research Graduate School, and of the Otto-von-Guericke Graduate School. He will be the IPC CoChair of the IFAC World Congress in Berlin in 2020. The main research interests of Rolf and his group are the development and application of systematic, theoretically well-founded analysis and control methods for complex systems. Main areas of interest are the development and application of optimization base control and estimation schemes, especially predictive control approaches, set-based approaches, system theoretic methods for problems from systems biology and biotechnology, especially for unraveling, modeling, and interactions, experimental design, and intervention/therapy design, as well as model validation, experimental design, and parameter estimation methods for nonlinear systems.