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Main Authors: Han, Shibo, Hou, Bonan, Zhang, Yuhao, Shi, Xiaotong, Zhao, Xingwei
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2503.20490
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_version_ 1866912295229063168
author Han, Shibo
Hou, Bonan
Zhang, Yuhao
Shi, Xiaotong
Zhao, Xingwei
author_facet Han, Shibo
Hou, Bonan
Zhang, Yuhao
Shi, Xiaotong
Zhao, Xingwei
contents In this article, a model predictive control (MPC) method is proposed for constrained linear systems to track bounded references with arbitrary dynamics. Besides control inputs to be determined, artificial reference is introduced as additional decision variable, which serves as an intermediate target to cope with sudden changes of reference and enlarges domain of attraction. Cost function penalizes both artificial state error and reference error, while terminal constraint is imposed on artificial state error and artificial reference. We specify the requirements for terminal constraint and cost function to guarantee recursive feasibility of the proposed method and asymptotic stability of tracking error. Then, periodic and non-periodic references are considered and the method to determine required cost function and terminal constraint is proposed. Finally, the efficiency of the proposed MPC controller is demonstrated with simulation examples.
format Preprint
id arxiv_https___arxiv_org_abs_2503_20490
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Model Predictive Control for Tracking Bounded References With Arbitrary Dynamics
Han, Shibo
Hou, Bonan
Zhang, Yuhao
Shi, Xiaotong
Zhao, Xingwei
Systems and Control
In this article, a model predictive control (MPC) method is proposed for constrained linear systems to track bounded references with arbitrary dynamics. Besides control inputs to be determined, artificial reference is introduced as additional decision variable, which serves as an intermediate target to cope with sudden changes of reference and enlarges domain of attraction. Cost function penalizes both artificial state error and reference error, while terminal constraint is imposed on artificial state error and artificial reference. We specify the requirements for terminal constraint and cost function to guarantee recursive feasibility of the proposed method and asymptotic stability of tracking error. Then, periodic and non-periodic references are considered and the method to determine required cost function and terminal constraint is proposed. Finally, the efficiency of the proposed MPC controller is demonstrated with simulation examples.
title Model Predictive Control for Tracking Bounded References With Arbitrary Dynamics
topic Systems and Control
url https://arxiv.org/abs/2503.20490