Session: 05-01 Advanced Controls for Propulsion Systems

Paper Number: 82219

82219 - Method of Analysis for Impact of Input Uncertainty Error Propagation in a Highly Nonlinear System: Applied to Modern Aircraft Engine 

Current methods for compressor vane control in a turbo-jet engine rely on measurements or estimates of compressor inlet temperatures and speed to determine the most favorable compressor stator vane angles over the course of an effectively infinite-horizon control decision process.  During each instance of this process, the stator vane angles must be adjusted with a regular frequency to manage compressor efficiency and stability over the course of a flight.  The optimality of these methods suffers from uncertainty in compressor inlet temperature, though the extent of deviation from optimality is unknown, as is the cost-benefit trade space for addressing this issue.  This is an example of a more general problem in systems engineering, which is to estimate the cost of uncertainty in information with respect to its effect on deviations from optimality in infinite- and indefinite-horizon decision processes subject to a stochastic state machine that determines decision outcome. This thesis will develop a methodology for (A) estimating the cost of uncertain information in these kinds of sequential decision processes, (B) characterizing the trade space associated with addressing this problem, and (C) application to the jet engine design refinement problem.

The paper will present flight data driven statistical spread of compessor inlet temperture ran through NPSS for uncertainty propagation system impact analysis.

Presenting Author: Timothy Castaldo Johns Hopkins University

Presenting Author Biography: Analytical engineer for Pratt and Whitney. This paper was produced for completion of Master of Science in Engineering, Systems Engineering from Johns Hopkins University.

Authors:

Timothy Castaldo Johns Hopkins University