Hans Georg Bock
Interdisciplinary Center for Scientific Computing, University of Heidelberg
Friday, November 25, 2016, 11:30
Room 02-016/18, Georges-Koehler-Allee 101, Freiburg 79110, Germany
We present numerical methods solving inverse optimal control problems as complex bi-level dynamic optimization problems: a nonlinear approximation problem on the upper level and a nonlinear optimal control problem (OCP) with discontinuities and mixed path-control constraints on the lower level. The OCP solution can be considered as a model that describes autonomous optimal processes in nature such as human gait. However, the optimal control model includes unknown parameters that need to be determined by fitting its solution to measurements in the upper level optimization. We develop a direct mathematical all-at-once approach for solving this new class of problems and apply this to derive biomechanical optimal control models for the gait of cerebral palsy patients from real-world motion capture data obtained by the Motion Lab of the Orthopedic University Hospital Heidelberg.