Optimal and Suboptimal Results in Full and Reduced Order Linear Filtering.
FRANK J SEILER RESEARCH LAB UNITED STATES AIR FORCE ACADEMY COLO
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This paper considers the synthesis of linear reduced order filters and the synthesis of linear full order filters with minimum complexity. The objective of a reduced order filter is to estimate a linear transformation of the state vector with a filter of lower dimension. This type of filter occurs frequently in applications. Several cases are studied. In a number of cases it is shown that singular arcs exist. In instances where certain filter parameters are not subject to optimization, it is shown that the remaining parameters can be optimized with a relatively simple procedure. Closed form solutions for a number of cases have been obtained. Author
- Theoretical Mathematics