Engineering structures, dynamic systems and mechanical components are affected by uncertainties, both caused by lack of sufficient knowledge of the systems (e.g., manufacturing defects and imperfections, heterogeneous material properties, etc.) or by natural unpredictable external events (e.g., earthquakes, wind loading, wave excitation, etc.). A design or control optimization procedure that does not take into account random variations of the model and environmental parameters, initial values, external loadings, payload, etc., may lead to fictitious results or even to unsafe components. Stochastic Optimization provides a well-suited framework to determine an optimal design or control coping with such uncertainties.
Hence, the original control and or optimization problem with unknown, random varying parameters must be replaced by an appropriate deterministic substitute problem incorporating the available a priori and sample information about the random parameters. Typical deterministic substitute problems demand then the minimization and/or restriction of expected costs (primary and recourse costs). Important examples of expected cost functions are failure probability functions.
The Special Session focuses on optimal design strategies that are robust against the involved uncertainties and risks. Hence, contributions on approximation concepts, simulation techniques, analytical and numerical methods to solve deterministic substitute problems, including reliability-based optimization problems are welcome as well as papers on applications to several concrete fields such as structural mechanics, feedback control, open-loop feedback control, nonlinear model prediction control under uncertainty.