%A FARAJZADEH-DEVIN Mohammad-Ghassem, HOSSEINI SANI Seyed Kamal %T Enhanced two-loop model predictive control design for linear uncertain systems %0 Journal Article %D 2021 %J Journal of Systems Engineering and Electronics %R 10.23919/JSEE.2021.000019 %P 220-227 %V 32 %N 1 %U {https://www.jseepub.com/CN/abstract/article_7885.shtml} %8 2021-02-25 %X

Model predictive controllers (MPC) with the two-loop scheme are successful approaches practically and can be classified into two main categories, tube-based MPC and MPC-based reference governors (RG). In this paper, an enhanced two-loop MPC design is proposed for a pre-stabilized system with the 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.