Improved Method for Development of Parsimonious Orthonormal Basis Filter Models

One of the major advantages of orthonormal basis filter (OBF) models is that they are parsimonious in
parameters. However, this is true only if appropriate type of filter and reasonably accurate dominant
poles of the system are used in developing the model. An arbitrary choice of filter type and poles may
lead to non-parsimonious model. While the selection of the type of filter may be simple if the damping
characteristics of the system are known, finding good estimates of the dominant pole(s) of the system
is not a trivial task. Another important advantage of OBF model is the fact that time delays can be easily
estimated and incorporated into the model. Currently, time delay of the system is estimated from the step
response of the OBF model using the tangent method. While this method is effective in estimating the
time delay of systems that can be accurately modeled by first order plus time delay (FOPTD) models, the
accuracy is low for systems with second- and higher-order dynamics. In this paper, a scheme is proposed
that will result in parsimonious OBF model and a better estimate of time delay starting from an arbitrary
set of poles.