Study Of Aviation Engine Parts, Performance Tracking Filter

This paper researches the engine component tracking filter for Model-Based Control system. The paper analyzes the sources of model-engine mismatch and designs an engine component tracking filter to minimize model-engine mismatch based on the Kalman filtering methods.The main content of this paper is the design approach for estimating engine component deviation parameters. The estimate parameters are used to tune the embedded model to minimize model-engine mismatch. Because the linearized engine model is time-invariant, it is well known that the Kalman filter gain matrix converges to a unique constant value if the system is both fully observable and controllable. Hence , the Kalman filter gain matrix can be computed off-line using MATLAB.The research uses compensating method to solve Kalman filtering divergence problems. This paper introduce an analytic method of incorporating state variable inequality constrains in the Kalman filter. The incorporating state variable inequality constrains can improves the estimation accuracy and strong the performance of restraining the noise.The research shows that the engine component tracking filter designed in this paper can work well with good convergence.