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Volume 11 Issue 7
Jul.  2024

IEEE/CAA Journal of Automatica Sinica

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B. Zhu, X. Yuan, L. Dai, and  Z. Qiang,  “Finite-time stabilization for constrained discrete-time systems by using model predictive control,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 7, pp. 1656–1666, Jul. 2024. doi: 10.1109/JAS.2024.124212
Citation: B. Zhu, X. Yuan, L. Dai, and  Z. Qiang,  “Finite-time stabilization for constrained discrete-time systems by using model predictive control,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 7, pp. 1656–1666, Jul. 2024. doi: 10.1109/JAS.2024.124212

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

doi: 10.1109/JAS.2024.124212
Funds:  This work was supported by the National Natural Science Foundation of China (62073015, 62173036, 62122014)
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  • 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.

     

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    Highlights

    • The proposed MPC guarantees finite-time convergence for systems subject to constraints
    • The proposed MPC is applicable to finite-time stabilization for constrained under-actuated vector systems
    • The proposed finite-time MPC is applicable for constrained nonlinear systems, and calculation for diffeomorphism can be avoided
    • The proposed finite-time MPC is applicable for multi-input systems, and its feasibility can be improved by augmentation

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