Abstract
Discusses system identification and model-based predictive control of multi-rate systems. In particular, the practically useful case of systems with fast manipulative variable sampling and slow output sampling is considered. The lifting method is used to analyze the multi-rate system in a state-space framework. A subspace identification algorithm, is first used to identify the lifted multi-rate system. The single-rate model at the faster sampling rate is then extracted from this estimated system and subsequently used for long-range predictive control. The fast-sampling rate model is used to estimate the outputs at inter-sample instants, using a minimum variance predictor. The estimated output is then used for model-based predictive control at the faster sampling rate. The performance of this controller is compared with the performance of the slow sample-rate scheme, and it is shown that the fast-rate controller has a significantly better performance.
Published Version
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