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This paper considers the state estimation of Markovian jump linear systems with random parameters and estimate feedback. The state estimate at the previous epoch is introduced into the dynamical model to depict some phenomena that the system evolvement may depend on the most recent estimate. Then, the linear minimum mean square error estimator is derived for the considered system. A filtering framework...
This paper presents the estimation problem of Markovian jump linear systems (MJLSs) with generalized unknown disturbances (GUDs). There exist multiple uncertainties including Markovian switching parameters and GUDs, along with traditional random noises. Here, the state transition of MJLS is treated as the jump from one vertex to another on a fixed polyhedron whose vertex represents a mode. Since the...
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