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• W164087171 abstract "This paper aims at solving the state filtering problem for linear systems with state constraints. Three classes of typical state constraints, i.e., linear equality, quadratic equality and inequality, are discussed. By using the linear relationships among different state variables, a reduced-order Kalman filter is derived for the system with linear equality constraints. Afterwards, such a solution is applied to the cases of the quadratic equality constraint and inequality constraints and the two constrained state filtering problems are transformed into two relative constrained optimization problems. Then they are solved by the Lagrangian multiplier and linear matrix inequality techniques, respectively. Finally, two simple tracking examples are provided to illustrate the effectiveness of the reduced-order filters." @default.
• W164087171 created "2016-06-24" @default.
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• W164087171 date "2013-08-01" @default.
• W164087171 modified "2023-10-05" @default.
• W164087171 title "Reduced-order Kalman filtering for state constrained linear systems" @default.
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• W164087171 doi "https://doi.org/10.1109/jsee.2013.00078" @default.
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