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A receding horizon control of discrete-time Markov jump linear systems with additive Gaussian measurement and process noise, and stochastic constraints is addressed. Given the availability of the underlying jump parameter, recursive equations for optimal state estimation that resemble Kalman filter equations are provided. The receding horizon control law is considered in state-feedback form. Under...
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