Frequency domain accuracy of approximate sampled-data models
Keywords: model, systems, domains, models, system, state, parameters, zeros, domain, errors, frequency, data, devices, analysis, expansions, sampling, loads, approximate, physical, Computational, Linear, digital, relative, Sampled, Taylor
Abstract
Accurate sampled-data models are required when a digital device interacts with a continuous-time system. Even though exact sampled models can be obtained for linear systems, simple approximate models are sometimes preferred in applications to reduce computational load or to preserve the role of physical parameters. In this paper we quantify the frequency domain relative error of three kinds of approximate sampled models: (i) simple models obtained by derivative approximations, (ii) models obtained including the asymptotic sampling zeros, and (iii) models obtained by a truncated Taylor expansion of the system state equations. In particular, we characterize the bandwidth where each of the proposed models provides the highest accuracy. © 2011 IFAC.
Más información
Título de la Revista: | IFAC Proceedings Volumes |
Volumen: | 18 |
Número: | PART 1 |
Editorial: | Elsevier |
Fecha de publicación: | 2011 |
Página de inicio: | 8711 |
Página final: | 8717 |
URL: | http://www.scopus.com/inward/record.url?eid=2-s2.0-84866760044&partnerID=q2rCbXpz |