Stochastic Optimization in Engineering
Optimizing a mechanical structure (e.g. a truss, a frame, etc.) or a dynamic system (e.g. an industrial or service robot), one has to cope with several random parameters (model parameters, disturbances, noise factors, etc.) not known in advance, at the planning stage, respectively. However, in most cases, prior and statistical information about the random parameter variations is available.
Hence, the present homepage yields information about analytical tools and numerical procedures for finding more robust optimal decisions, i.e., optimal designs or optimal controls being insensitive with respect to random parameter variations. This can be achieved by applying stochastic optimization methods incorporating the available prior and statistical information about the random parameter variations into the optimization process.