The engineering challenges in Systems of Systems ( SoS ) are in the focus of many research and innovation efforts as these systems are believed to have become the next generation of technical systems which will offer more efficient operation by making use of extensive information exchange between their constituent systems. This thesis presents a Modelica-based simulation and validation framework ( SVF ) that supports the development of distributed control and optimization algorithms of systems of systems by providing a structured, plug-and-play approach for the validation of such algorithms on simulation models of SoS. The framework offers standardized interfaces to which simulation models and control and optimization algorithms that are implemented in different formalisms can be connected. A key element is that in the framework the validation models which represent the real system and models used in the algorithms can be different. The ready-to-use SoS simulation model, i. e. the set of validation models and controller components which are connected by standardized interfaces is generated automatically by a model generator module. To that end, an XML-based configuration file which includes detailed information about the information exchange structure between the validation models and the control and optimization algorithms provides the required information for the model generation step. The SVF supports control and optimization algorithms written in C, Python and MA-LAB. Besides validation models written in Modelica, models from modeling and simulation tools that are supported by the Functional Mock up Interface (FMI) can be integrated into the framework by co-simulation. The capabilities of the SVF are demonstrated on four use cases, two of which come from the process industries.weiterlesen