Titlebook: Sampled-Data Models for Linear and Nonlinear Systems; Juan I. Yuz,Graham C. Goodwin Book 2014 Springer-Verlag London 2014 Data Sampling.Di

天空

Background on Sampling of Signalsish notation. In particular, the continuous and discrete-time Fourier transform are defined. Sampling of signals and the aliasing effect are then presented. Finally, the use of antialiasing filters and reconstruction of signals from samples are also discussed.

隐藏

演绎

Solace

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beta-cells

Robustnessus-time model back to lower frequencies is discussed. This aliasing effect may impact the assumptions regarding the high frequency behaviour of the system due to unmodeled high frequency poles or zeros. In particular, the location of asymptotic sampling zeros rely on these high frequency characteris

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Applications of Approximate Sampled-Data Models in Estimation and Controlnlinear systems. Applications include state estimation and feedback control for linear systems, sampled-data state feedback control for nonlinear systems, continuous-time system identification from sampled data, and sampled-data predictive control of an electrical machine.

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Asymptotic Sampling Zeros for Linear Stochastic Systemstance is the existence of sampling zeros in the sampled-data power spectral density. These can be asymptotically characterized as the sampling period goes to zero. The results are the stochastic extension of the results presented in Chap. . for the deterministic case.

Cleave

Generalised Sampling Filters output power spectral density depend on the choice of this filter. In particular, we present a generalized sampling filter design, such that the sampling zeros of the sampled output power spectral density are asymptotically assigned. This analysis is the stochastic counterpart of generalized hold f