Abstract: Non-uniformly sampled systems are widely found in industry. In these systems the process output is sampled and the control input is generated at non-uniformly distributed time instants. In this paper, an optimal residual generator is developed for fault detection in non-uniformly sampled systems. In the direct approach used here, the intersample behavior of fault and disturbance is ca...

This paper looks at the problem of system identification from non-uniformly sampled input-output data. It describes how refined instrumental variable estimators can be derived to directly identify the parameters of continuous-time output error and Box-Jenkins transfer function models from irregularly sampled data. Monte Carlo simulation analysis is used to illustrate the properties of the propo...

This paper concerns the subject of identi cation of continuous-time output error (OE) models based on non-uniformly sampled output data. The exact method for doing this is well known in the time-domain, where the continuous-time system is discretized, simulated and the result is tted in a mean square sense to measured data. The material presented here is based on a method proposed in a sister p...

This contribution reviews theory, algorithms, and validation results for system identification of continuous-time state-space models from finite inputoutput sequences. The algorithms developed are autoregressive methods, methods of subspace-based model identification and stochastic realization adapted to the continuous-time context. The resulting model can be decomposed into an input-output mod...

This paper treats the identification of continuous-time output error (OE) models based on sampled data. The exact method for doing this is well known both for data given in the time domains, but this approach becomes somewhat complex, especially for non-uniformly sampled data. In this paper we assume that the system is fed with a zero order hold input signal and that the sampling rate is so hig...