Square-root arrays and Chandrasekhar recursions for H∞ problems
Using their previous observation that H∞ filtering coincides with Kalman filtering in Krein space the authors develop square-root arrays and Chandrasekhar recursions for H∞ filtering problems. The H∞ square-root algorithms involve propagating the indefinite square-root of the quantities of interest and have the property that the appropriate inertia of these quantities is preserved. For systems that are constant, or whose time-variation is structured in a certain way, the Chandrasekhar recursions allow a reduction in the computational effort per iteration from O(n^3) to O(n^2), where n is the number of states. The H∞ square-root and Chandrasekhar recursions both have the interesting feature that one does not need to explicitly check for the positivity conditions required of the H∞ filters. These conditions are built into the algorithms themselves so that an H∞ estimator of the desired level exists if, and only if, the algorithms can be executed.
© 1994 IEEE. This research was supported by the Advanced Research Projects Agency of the Department of Defense monitored by the Air Force Office of Scientific Research under Contract F49620-93-1-0085.
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