Model predictive controllers (MPCs) with two-loop scheme are successful approaches practically and can be classified into two main categories, tube-based MPCs and MPC-based Reference Governors (RGs). In this paper an enhanced two-loop MPC design is proposed for a pre-stabilized system with bounded uncertainty subject to the input and state constraints. The proposed method offers less conservatism than the tube-based MPC methods by enlarging the restricted input constraint. Contrary to the MPC-based RGs, the investigated method improves tracking performance of the pre-stabilized system while satisfying the constraints. Additionally, the robust global asymptotic stability of the closed-loop system is guaranteed in a novel procedure with terminal constraint relaxation. Simulation of the proposed method on a servo system shows its effectiveness in comparison to the others.

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