High-Speed Machining (HSM) spindles equipped with Active Magnetic Bearings (AMBs) have been envisioned to be capable of automated self-identification and self-optimization in efforts to accurately calculate parameters for stable high-speed machining operation. With this in mind, this work presents rotor model development accompanied by automated model-updating methodology followed by updated model validation. The model updating methodology is developed to address the dynamic inaccuracies of the nominal open-loop plant model when compared with experimental open-loop transfer function data obtained by the built in AMB sensors. The nominal open-loop model is altered by utilizing an unconstrained optimization algorithm to adjust only parameters that are a result of engineering assumptions and simplifications, in this case Young's modulus of selected finite elements. Minimizing the error of both resonance and anti-resonance frequencies simultaneously (between model and experimental data) takes into account rotor natural frequencies and mode shape information. To verify the predictive ability of the updated rotor model, its performance is assessed at the tool location which is independent of the experimental transfer function data used in model updating procedures. Verification of the updated model is carried out with complementary temporal and spatial response comparisons substantiating that the updating methodology is effective for derivation of open-loop models for predictive use.© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.