Output Regulation for Linear Sampled Data Systems Using a Realizable Reconstruction Filter

A realizable reconstruction filter (RRF) is a tracker that can exactly reproduce a continuous signal from its samples. It assumes an accurate knowledge of the linear time invariant process generator (or exosystem) of the signal. In this paper, we use RRF to solve the output regulation problem for a sampled data system. The scheme relies on discrete-time equivalent of the plant. This leads to entire controller/observer design in discrete time. The paper focuses on an important class of signals to be treated as references, i.e., signals composed of multiple sinusoids. Uncertain systems are also discussed as a standard topic of the regulation problem. Stability analysis followed by example concludes the exposition.

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