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Closed-loop output error identification algorithms for nonlinear plants

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A family of algorithms for the identification of continuous time nonlinear plants operating in closed-loop is presented. An adjustable output error type predictor is parametrized in terms of the existing controller and the estimated plant model. The algorithms are derived from stability considerations in the absence of noise and assuming that the plant model is in the model set. Subsequently the algorithms are analyzed in the presence of noise and when the plant model is not in the model set.

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Proceedings of the IEEE Conference on Decision and Control

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