A parametric extension of mixed time/frequency robust identification

A parametric extension to the time/frequency robust identification framework is presented. The results can be applied to stable linear time-invariant systems on which time and/or frequency experiments have been performed. The parametric portion of the model should be affine in the unknown parameters, which includes practical applications such as flexible structures. The consistency problem is cast as a constrained finite-dimensional convex optimization problem that can be formulated as a linear matrix inequality. The proposed procedure provides an interpolating identification algorithm, convergent and optimal up to a factor of two (with respect to central algorithms).