Accession Number : ADA311712
Title : Robust Discrete Estimation of the Space Shuttle Main Engine.
Descriptive Note : Master's thesis,
Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH
Personal Author(s) : Jensen, Jonathan A.
PDF Url : ADA311712
Report Date : JUN 1996
Pagination or Media Count : 70
Abstract : This thesis applies recently developed robust H at infinity, or game theoretic, estimation algorithms to the Space Shuttle Main Engine (SSME). The objective is to process noisy, inaccurate sensor data in order to obtain estimates of pressure in the main combustion chamber and the oxygen to fuel mixture ratio. Each of the estimators are based on discrete time, state space models of the SSME, and employ varying levels of robustness when solving the H at infinity estimation problem. Two general problems are examined. First, H at infinity minimax estimators are derived for the case where the plant dynamics are accurately known, but the noise statistics are uncertain. The effects of various noise inputs are explored. Next, robust H at infinity estimators are designed when plant, sensor, and noise uncertainties are present. It is shown that the performance of the normally optimal Kalman filter degrades considerably in the presence of model uncertainty. By contrast, the robust H at infinity estimators perform well for the entire range of plant, sensor, and noise models considered.
Descriptors : *PRESSURE GAGES, *LIQUID PROPELLANT ROCKET ENGINES, ALGORITHMS, UNCERTAINTY, DETECTORS, KALMAN FILTERING, THESES, ESTIMATES, SPACE SHUTTLES, COMBUSTION CHAMBERS, NOISE, MINIMAX TECHNIQUE.
Subject Categories : Liquid Propellant Rocket Engines
Distribution Statement : APPROVED FOR PUBLIC RELEASE