This talk is dedicated to a common descent method designed for nonsmooth multiobjective optimization problems (MOPs) with objective functions defined on a general Hilbert space that are locally Lipschitz continuous. The only strategy to handle nonsmooth MOPs in infinite dimensions besides the presented method relies on scalarization techniques, which are not suitable for MOPs with nonconvex...
We present a method for the approximate propagation of mean and covariance of a probability distribution through ordinary differential equations (ODE) with discontinuous right-hand side. For piecewise affine systems, a normalization of the propagated probability distribution at every time step allows us to analytically compute the expectation integrals of the mean and covariance dynamics while...
We utilize the probability distributions of the future location of moving obstacles to aid in the maneuver planning of autonomous vehicles. The result is an objective function and necessary derivatives to solve optimal control problems in a multi-shooting scheme with shooting nodes on an equidistant time grid. We evaluate the proposed objective function in different scenarios featuring...
In this talk, we propose a benchmark problem for numerical nonsmooth optimal control, tailored for systems with autonomous state jumps. In particular, these challenges are posed by mechanical systems with inherent nonsmoothness, characterized by abrupt jumps in both states and dynamics. Our proposed benchmark scenario involves accelerating a bicycle along an uneven mountain bike track without...
Several formulations for robustified optimization problems incorporate first-order derivatives of the original objective. In dynamic optimization settings, this usually involves the computation of sensitivities w.r.t. initial values and parameters of the underlying differential model.
We present the toolkit IFDIFF [1] for integration and sensitivity generation in parameterized implicitly...
Column liquid chromatography plays an important role in the downstream processing of biopharmaceuticals, where the goal is to capture and purify a target protein from a mixture. Our goal is to employ a model-based approach for process optimization to improve the quality of the product, while also achieving further economical and ecological benefits.
Rate models in combination with suitable...
