This paper presents a method for discrete-time bilinear state-space model identification from a single set of input-output data. The initial state can be unknown. By extending the interaction matrix formulation from linear to bilinear state-space models, the bilinear system state is expressed in terms of input-output measurements. This relationship is used to convert the bilinear model to an Equivalent Linear Model (ELM) which can be identified by any linear identification method such as a superspace method presented here. The bilinear state-space model is then extracted from the identified ELM. A companion paper deals with the identification of nonlinear input-output models instead of state-space models for a bilinear system using the same interaction matrix approach.
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