Enhanced two-loop model predictive control design for linear uncertain systems

• 作者: Mohammad-Ghassem FARAJZADEH-DEVIN Seyed Kamal HOSSEINI SANI
• 来源期刊: 系统工程与电子技术（英文版）
• 年，卷（期）: 2021,（1）
• 所属期刊栏目: CONTROL THEORY AND APPLICATION
• 页码范围: 220-227
• 页数: 8页
• 语种: 英文
• DOI: 10.23919/JSEE.2021.000019

摘要

Model predictive controllers (MPC) with the two-loop scheme are successful approaches practically and can be clas-sified 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 con-straints. The proposed method offers less conservatism than the tube-based MPC methods by enlarging the restricted input con-straint. 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.