Estimation for advanced technology engines

Abstract

An estimation algorithm for nonlinear transient operation of multivariable gas turbine engines was developed and evaluated. Kalman methodology and model-mismatch compensation procedures were employed in defining the filtering logic. The estimation algorithm was evaluated by application to noise-corrupted measurement data generated by a nonlinear digital dynamic F100/F401 engine simulation. Estimation of unmeasurable as well as measurable key engine variables from (1) nominalengine data, (2) degraded-engine data, and (3) engine data with off-nominal noise statistics was evaluated. Results obtained indicate that the nonlinear estimation algorithm provides a viable approach to estimating key engine variables under realistic operating conditions.