This paper describes the application of a recursive least squares algorithm to identify a laboratory turbogenerator system. The algorithm was initially tested in a computer simulation, which indicated that identified low-order models can represent the small-signal dynamics of a non-linear system more accurately than the corresponding linearized analytical models. This was confirmed by laboratory tests, which clearly showed the difficulty of representing the system by analytical models, and the substantial improvement obtained by identification