Finite-Time Stabilization for Constrained Discrete-time Systems by Using Model Predictive Control  

作　　者：Bing Zhu Xiaozhuoer Yuan Li Dai Zhiwen Qiang 

机构地区：[1]IEEE [2]the Seventh Research Division,Beihang University,Beijing 100191,China [3]the School of Automation,Beijing Institute of Technology,Beijing 100081,China

出　　处：《IEEE/CAA Journal of Automatica Sinica》2024年第7期1656-1666,共11页自动化学报（英文版）

基　　金：supported by the National Natural Science Foundation of China (62073015,62173036,62122014)。

摘　　要：In this paper, a model predictive control(MPC)framework is proposed for finite-time stabilization of linear and nonlinear discrete-time systems subject to state and control constraints. The proposed MPC framework guarantees the finite-time convergence property by assigning the control horizon equal to the dimension of the overall system, and only penalizing the terminal cost in the optimization, where the stage costs are not penalized explicitly. A terminal inequality constraint is added to guarantee the feasibility and stability of the closed-loop system.Initial feasibility can be improved via augmentation. The finite-time convergence of the proposed MPC is proved theoretically,and is supported by simulation examples.

关 键 词：CONSTRAINTS deadbeat control finite-time stabilization model predictive control(MPC) 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]