Abstract
AbstractWe propose a procedure for identification of reduced‐order bilinear models from time‐domain data, i.e., sampled values of the control input and of the observed output. To accomplish this, we require two sets of data corresponding to the response of the system to two differently‐scaled step functions, as control inputs. Then, the Markov parameters for two time‐varying linear models are extracted, and from this information, we are able to infer a reduced‐order bilinear model.
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