A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multivariable iterative search routine that seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared with the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy.
Skip Nav Destination
Article navigation
March 2010
Research Papers
Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation
Donald L. Simon,
Donald L. Simon
NASA Glenn Research Center
, 21000 Brookpark Road, MS 77-1 Cleveland, OH 44135
Search for other works by this author on:
Sanjay Garg
Sanjay Garg
NASA Glenn Research Center
, 21000 Brookpark Road, MS 77-1 Cleveland, OH 44135
Search for other works by this author on:
Donald L. Simon
NASA Glenn Research Center
, 21000 Brookpark Road, MS 77-1 Cleveland, OH 44135
Sanjay Garg
NASA Glenn Research Center
, 21000 Brookpark Road, MS 77-1 Cleveland, OH 44135J. Eng. Gas Turbines Power. Mar 2010, 132(3): 031601 (10 pages)
Published Online: December 2, 2009
Article history
Received:
March 20, 2009
Revised:
April 27, 2009
Online:
December 2, 2009
Published:
December 2, 2009
Citation
Simon, D. L., and Garg, S. (December 2, 2009). "Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation." ASME. J. Eng. Gas Turbines Power. March 2010; 132(3): 031601. https://doi.org/10.1115/1.3157096
Download citation file:
Get Email Alerts
Experimental Identification Of Blade Tip Rub Forces At Engine Relevant Temperatures And Speeds
J. Eng. Gas Turbines Power
Study Of Tandem Rotor Dual Wake Interaction With Downstream Stator Under Unsteady Numerical Approach
J. Eng. Gas Turbines Power
Experimental Design Validation of a Swirl-Stabilized Burner With Fluidically Variable Swirl Number
J. Eng. Gas Turbines Power (April 2025)
Experimental Characterization of a Bladeless Air Compressor
J. Eng. Gas Turbines Power (April 2025)
Related Articles
Application of an Optimal Tuner Selection Approach for On-Board Self-Tuning Engine Models
J. Eng. Gas Turbines Power (April,2012)
An Optimal Orthogonal Decomposition Method for Kalman Filter-Based Turbofan Engine Thrust Estimation
J. Eng. Gas Turbines Power (January,2008)
Aircraft Turbofan Engine Health Estimation Using Constrained Kalman Filtering
J. Eng. Gas Turbines Power (April,2005)
Hybrid Kalman Filter Approach for Aircraft Engine In-Flight Diagnostics: Sensor Fault Detection Case
J. Eng. Gas Turbines Power (July,2007)
Related Proceedings Papers
Related Chapters
Machine Learning Methods for Data Assimilation
Intelligent Engineering Systems through Artificial Neural Networks, Volume 20
Position Controller for DC Motor Using PI Controller with KALMAN Filter
International Conference on Computer Technology and Development, 3rd (ICCTD 2011)
A Novel Approach for LFC and AVR of an Autonomous Power Generating System
International Conference on Mechanical Engineering and Technology (ICMET-London 2011)