TY  - JOUR
AV  - none
Y1  - 2011///
KW  - Multi-step; Orthonormal basis; Prediction model; Simulation model; System identifications
KW  -  Estimation; Forecasting; Mathematical models; Poles; Time delay
KW  -  Computer simulation
SP  - 36
A1  - Tufa, L.D.
A1  - Ramasamy, M.
A1  - Shuhaimi, M.
VL  - 21
N1  - cited By 15
TI  - Improved method for development of parsimonious orthonormal basis filter models
IS  - 1
JF  - Journal of Process Control
SN  - 09591524
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-78751581546&doi=10.1016%2fj.jprocont.2010.10.001&partnerID=40&md5=cf499148b824aa9e9752eff51dd8fcfe
EP  - 45
N2  - 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. © 2010 Elsevier Ltd. All rights reserved.
ID  - scholars2371
ER  -