15th Triennial World Congress of the International Federation of Automatic Control
  Barcelona, 21–26 July 2002 
INFINITE-IMPULSE AND FINITE-IMPULSE RESPONSE FILTERS FOR CONTINUOUS-TIME PARAMETER ESTIMATION
Peter J Gawthrop* Liuping Wang**
* Centre for Systems and Control and Department of Mechanical
Engineering, University of Glasgow, Glasgow. G12 8QQ Scotland.
P.Gawthrop@eng.gla.ac.uk
** Centre for Integrated Dynamics and Control, Dept. of Electrical and
Computer Engineering, The University of Newcastle, University Drive,
Callaghan, 2308, Australia
wangl@hartley.newcastle.edu.au

This paper examines two classes of algorithms that estimate a continuous time ARX type of models from discrete data: one is based on infinite impulse response (IIR) filters while the other is based on finite impulse response (FIR) filters. The IIR filters use continuous time state variable filters, and discretisation is performed on the filtered derivatives. In contrast, the FIR filters are in a discrete form with carefully chosen coefficients to approximate the derivatives of the continuous time variables. The strength and weakness of each approach are discussed and demonstrated by a set of simulation examples.
Keywords: continuous time systems, least squares estimation, parameter estimation
Session slot T-Tu-E02: Continuous-time model identification: methods and applications/Area code 3a : Modelling, Identification and Signal Processing