Abstract
This chapter explores the relationship between sampled-data models and the associated continuous-time system. In particular, the chapter shows how the sampled-data model relates to the original continuous-time model, when a fast sampling rate is used. It is shown that a simple reparameterization of the sampled model in the so called incremental (or delta) form, is required in order to recover the continuous-time model when the sampling period goes to zero.
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Additional background on incremental models can be found in
Feuer A, Goodwin GC (1996) Sampling in digital signal processing and control. Birkhäuser, Boston
Goodwin GC, Middleton RH, Poor HV (1992) High-speed digital signal processing and control. Proc IEEE 80(2):240–259
Mansour M (1993) Stability and robust stability of discrete-time systems in the δ-transform. In: Jamshidi M et al. (eds) Fundamentals of discrete-time systems: a tribute to Prof. Eliahu I. Jury. TSI Press, San Antonio
Middleton RH, Goodwin GC (1990) Digital control and estimation. A unified approach. Prentice Hall, Englewood Cliffs
Premaratne K, Jury EI (1994) Tabular method for determining root distribution of delta-operator formulated real polynomials. IEEE Trans Autom Control 39(2):352–355
Salgado ME, Middleton RH, Goodwin GC (1988) Connection between continuous and discrete Riccati equations with applications to Kalman filtering. IEE Proc Part D, Control Theory Appl 135(1):28–34
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© 2014 Springer-Verlag London
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Yuz, J.I., Goodwin, G.C. (2014). Incremental Sampled-Data Models. 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_4
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DOI: https://doi.org/10.1007/978-1-4471-5562-1_4
Publisher Name: Springer, London
Print ISBN: 978-1-4471-5561-4
Online ISBN: 978-1-4471-5562-1
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