On the Identification of Continuous Time Dynamical Systems
1988 (English)Report (Other academic)
The aim of this paper is to give insights into the problem of estimating continuous time systems based on discrete time measurements. To understand how a high sampling rate will influence our estimate, we will study continuous time prediction error methods. This paper contains an overview of continuous time prediction error methods. These results will be a basis for understanding what happens in case of fast sampling and discrete time measurements. These issues are discussed. Since a discrete time prediction error method will converge to a continuous time prediction error method as the sampling interval decrease, we can use the insights from the theory of continuous time prediction error methods to avoid some difficulties such as approximate differentiation. It is shown that it is less sensitive to use parameterizations that can be viewed as approximations of continuous time parameterizations, e.g. the coefficient of the numerator and denominator polynomial in the so-called Delta operator. An important aspect that will limit the choice of sampling rate is the effects of quantization errors in A/D converters. For fast sampling intervals the effects of quantization errors can be drastic, and consequently destroy the estimates.
Place, publisher, year, edition, pages
Linköping: Linköping University , 1988. , 6 p.
LiTH-ISY-I, ISSN 8765-4321 ; 905
Control Systems, Discrete Time, Sampled Data, Data Conversion, Analog to Digital, Mathematical Techniques, Continuous Time System, Fast Sampling, Parameter Estimation, Quantization Errors, System Identification, Systems Science and Cybernetics
IdentifiersURN: urn:nbn:se:liu:diva-104208OAI: oai:DiVA.org:liu-104208DiVA: diva2:695360