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<p>In this article, considering the general existence of the time delay phenomenon that affects the system stability in uncertain constrained discrete linear system, we propose an optimal robust tube-based model predictive control (RTMPC) strategy to simultaneously deal with the external disturbances and time delays. Firstly, the robust control constraints for a nominal linear system with time delays are designed to address the uncertainties in the robust MPC algorithm. Compared with classical robust MPC methods, these constraints can limit the state of the nominal system to a small range, thereby reducing the system conservatism and enhancing robustness to system uncertainty. In addition, due to the consideration of time delay states in the proposed robust controller, the system has memory ability during optimization calculation, which can improve system control performance to a certain extent. Finally, the effectiveness of the proposed RTMPC strategy are demonstrated through the comparative simulations.</p>

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A Robust Tube-based MPC Strategy With the Enhanced Memory State Feedback for Uncertain Constrainted Linear Systems With Time Delays

  • 期刊论文

  • 发表日期：

    2025年3月10日

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  • Zhuoer An,
  • Xinghua Liu,
  • Gaoxi Xiao,
  • Yu Kang,
  • Peng Wang

摘要

In this article, considering the general existence of the time delay phenomenon that affects the system stability in uncertain constrained discrete linear system, we propose an optimal robust tube-based model predictive control (RTMPC) strategy to simultaneously deal with the external disturbances and time delays. Firstly, the robust control constraints for a nominal linear system with time delays are designed to address the uncertainties in the robust MPC algorithm. Compared with classical robust MPC methods, these constraints can limit the state of the nominal system to a small range, thereby reducing the system conservatism and enhancing robustness to system uncertainty. In addition, due to the consideration of time delay states in the proposed robust controller, the system has memory ability during optimization calculation, which can improve system control performance to a certain extent. Finally, the effectiveness of the proposed RTMPC strategy are demonstrated through the comparative simulations.