A contribution to parameter identification in infinite-dimensional systems

Parameter identification in infinite-dimensional systems with lumped measurements is considered. The proposed method is based on a convolutional input-output relation of the underlying system of partial differential equations. The derivation of this input-output relation is presented in a framework involving (ultra-)distributions. The unknown parameters are determined by minimizing an associated error functional.