Time domain control oriented model validation using coprime factor perturbations

This paper addresses the time domain model validation problem for uncertainty models that are structured using coprime factorizations. A model validation technique is proposed in which measurement data is used to validate a derived uncertainty model. Newly proposed model validation techniques are based on a fractional representation approach and addresses the problem of correlation between the input and output signals inherent to closed-loop systems. The model validation problem for coprime factorizations is considered for closed-loop time domain data in the cases of noise-free and noisy measurements where the results rely on a linear relationship between input and output data.