A black-box method for parametric model order reduction based on matrix interpolation with application to simulation and control

This thesis deals with model order reduction of parameter-dependent systems based on interpolation of locally reduced system matrices. A Black-Box method is proposed that automatically determines the optimal design parameters and delivers a reduced system with desired accuracy. In addition, the method is extended to stability-preservation and interpolation for high-dimensional parameter spaces. The benefit of the method is demonstrated for examples from simulation and control.