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In this paper, the model predictive control based on the state estimation for a constrained system is investigated. By modifying the constraints for the predictive state, the control sequence becomes feasible for the real system, i.e., the system state is guaranteed to be in the constraint domain. Its also proved that the close-loop system is asymptotically stable and the system state converges to the origin. The conclusion is verified through simulation.