Evolutionary Computation for Model Order Reduction with Parametric Generalised SPA

In this paper evolutionary computation algorithms are applied to select optimal parameters in model order reduction for linear systems. In particular a parameterized set of reduced order model is obtained by using a Parametric Generalised Singular Perturbation Approximation of a balanced realization. The optimization algorithm is then used to select the parameter set that minimize a suitable performance index. Numerical examples are reported in comparison with other model order reduction methods.