Abstract
This chapter develops various approximate discrete-time models for general linear deterministic systems. It is always possible to obtain an exact sampled models for linear systems. However, approximate models are treated here to provide insights into the structure of discrete-time models, to obtain simpler models, and to be able to construct similar approximate sampled models for nonlinear systems, later in the book. We present models based on simple Euler integration, on the inclusion of asymptotic sampling zeros, on up-sampling, on normal forms and on truncated Taylor series expansions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Further Reading
Further information regarding corrected asymptotic sampling zeros can be found in
Blachuta MJ (1999a) On approximate pulse transfer functions. IEEE Trans Autom Control 44(11):2062–2067
Blachuta MJ (1999b) On zeros of pulse transfer functions. IEEE Trans Autom Control 44(6):1229–1234
An application of up-sampled models can be found in
Cea M, Goodwin GC (2010) Up-sampling strategies in sampled data nonlinear filtering. In: 49th IEEE conference on decision and control
Further information regarding relative errors for approximate linear sampled-data models is given in
Goodwin GC, Yuz JI, Agüero JC (2008) Relative error issues in sampled data models. In: 17th IFAC world congress, Seoul, Korea
Yucra E, Yuz JI (2011) Frequency domain accuracy of approximate sampled-data models. In: 18th IFAC world congress, Milan, Italy
Normal forms for linear (and nonlinear) systems are described in detail in
Isidori A (1995) Nonlinear control systems, 3rd edn. Springer, Berlin
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag London
About this chapter
Cite this chapter
Yuz, J.I., Goodwin, G.C. (2014). Approximate Models for Linear Deterministic Systems. In: Sampled-Data Models for Linear and Nonlinear Systems. Communications and Control Engineering. Springer, London. https://doi.org/10.1007/978-1-4471-5562-1_8
Download citation
DOI: https://doi.org/10.1007/978-1-4471-5562-1_8
Publisher Name: Springer, London
Print ISBN: 978-1-4471-5561-4
Online ISBN: 978-1-4471-5562-1
eBook Packages: EngineeringEngineering (R0)