Title

Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering

Document Type

Article

Publication Date

4-2005

Publication Title

Journal of Engineering for Gas Turbines and Power

Abstract

Kalman filters are often used to estimate the state variables of a dynamic system. However in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state-variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter This paper develops an analytic method of incorporating state-variable inequality constraints in the Kalman filter. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The incorporation of state-variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results obtained from application to a turbofan engine model. This model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering.

Original Citation

Simon, D., Simon, D.L. (2005). Aircraft turbofan engine health estimation using constrained Kalman filtering. Journal of Engineering for Gas Turbines and Power 127 (2), 323-328. DOI:10.1115/1.1789153

DOI

10.1115/1.1789153

Volume

127

Issue

2