Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering

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...

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Constrained Kalman filtering via density function truncation for turbofan engine health estimation

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...

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H∞ Filtering with Inequality Constraints for Aircraft Turbofan Engine Health Estimation

H∞ filters (also called minimax filters) can estimate the state variables of a dynamic system. However, in the application of state estimators, 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 state es...

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A comparison of filtering approaches for aircraft engine health estimation

Different approaches for the estimation of the states of linear dynamic systems are commonly used, the most common being the Kalman filter. For nonlinear systems, variants of the Kalman filter are used. Some of these variants include the LKF (linearized Kalman filter), the EKF (extended Kalman filter), and the UKF (unscented Kalman filter). With the LKF and EKF, performance varies depending on ...

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Discussion on: "Kalman Filter Constraint Switching for Turbofan Engine Health Estimation"

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. Rece...

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Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering

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