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Modified Multiple Model Adaptive Estimation (M3AE) for Simultaneous Parameter and State Estimation
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This is a AIR FORCE INST OF TECH WRIGHT-PATTERSONAFB OH SCHOOL OF ENGINEERING report procured by the Pentagon and made available for public release. It has been reproduced in the best form available to the Pentagon. It is not spiral-bound, but rather assembled with Velobinding in a soft, white linen cover. The Storming Media report number is A213443. The abstract provided by the Pentagon follows: In many estimation problems, it is desired to estimate system states and parameters simultaneously. However, inherent to traditional estimation architectures of the past, the designer has had to make a trade-off decision between designs intended for accurate state estimation versus designs concerned with accurate parameter estimation. This research develops one solution to this trade-off decision by proposing a new architecture based on Kalman filtering (KF) and Multiple Model Adaptive Estimation (MMAE) techniques. This new architecture, the Modified-MMAE (M3AE), exploits the benefits of an MMAE designed for accurate parameter estimation, and yet performs at least as well in state estimation as an MMAE designed for accurate state estimation. The M3AE accomplishes the simultaneous estimation task by providing accurate state estimates from a single KF designed to accept accurate parameter estimates from the MMAE. Additionally, an M3AE approximate covariance analysis capability is developed, giving the designer a valuable design tool for analyzing and predicting M3AE performance before actually implementing the M3AE and conducting a time-consuming full-scale Monte Carlo performance analysis. Finally, the M3AE architecture is applied to two existing research examples to demonstrate the performance improvement over that of conventional MMAEs. The first example involves a simple second-order mechanical translational system, in which the system's natural frequency is the uncertain parameter.
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