Identification of LFT Structured Descriptor Systems with Slow and Non-uniform Sampling
–arXiv.org Artificial Intelligence
Time domain identification is studied in this paper for parameters of a continuous-time multi-input multi-output descriptor system, with these parameters affecting system matrices through a linear fractional transformation. Sampling is permitted to be slow and non-uniform, and there are no necessities to satisfy the Nyquist frequency. This model can be used to described the behaviors of a networked dynamic system, and the obtained results can be straightforwardly applied to a state-space model. An explicit formula is obtained respectively for the transient and steady-state response of the system stimulated by an arbitrary signal. Some relations have been derived between the system steady-state response and its transfer function matrix. A parametric estimation algorithm is suggested.
arXiv.org Artificial Intelligence
Jun-30-2024
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