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<p>This paper presents a novel approach to solve the 3-D trajectory tracking problem for a remotely operated vehicle (ROV) using robust multistage nonlinear model predictive control (multistage NMPC) with symbolic computation. The proposed multistage control structure enhances the robustness of NMPC and improves control performance under environmental disturbances. The validity and robustness of the multistage NMPC approach are demonstrated through simulations conducted on a commercial-scale ROV operating under disturbances. Results show that the multistage NMPC approach outperforms the standard NMPC method and impressively is almost as good as the perfect information NMPC in solving the 3-D trajectory tracking problem for a ROV. Symbolic computation is employed to facilitate the implementation of the multistage NMPC approach. Specifically, symbolic computation is used to obtain the Jacobian and Hessian matrices required for the multistage NMPC method. The sensitivity analysis on the terminal cost shows that an appropriate terminal cost enhances the multistage NMPC controller performance, allowing for shorter prediction horizons without compromising accuracy. Simulations reveal that higher-frequency disturbances are easier to “average out” for both standard and multistage NMPC. Yet, the multistage NMPC approach yields much better accuracy across all tested frequencies. The simulations demonstrate that the proposed multistage NMPC approach can be solved for the 3-D trajectory tracking problem in real time.</p>

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Symbolic computation-based robust multistage NMPC for 3-D trajectory tracking of a ROV

  • 期刊论文

  • 发表日期：

    2025年2月21日

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  • Xiaoyong Jiang,
  • Zhenhai Yang,
  • Yuxi Wu,
  • Qiyao Zhu,
  • Shutian Xu

摘要

This paper presents a novel approach to solve the 3-D trajectory tracking problem for a remotely operated vehicle (ROV) using robust multistage nonlinear model predictive control (multistage NMPC) with symbolic computation. The proposed multistage control structure enhances the robustness of NMPC and improves control performance under environmental disturbances. The validity and robustness of the multistage NMPC approach are demonstrated through simulations conducted on a commercial-scale ROV operating under disturbances. Results show that the multistage NMPC approach outperforms the standard NMPC method and impressively is almost as good as the perfect information NMPC in solving the 3-D trajectory tracking problem for a ROV. Symbolic computation is employed to facilitate the implementation of the multistage NMPC approach. Specifically, symbolic computation is used to obtain the Jacobian and Hessian matrices required for the multistage NMPC method. The sensitivity analysis on the terminal cost shows that an appropriate terminal cost enhances the multistage NMPC controller performance, allowing for shorter prediction horizons without compromising accuracy. Simulations reveal that higher-frequency disturbances are easier to “average out” for both standard and multistage NMPC. Yet, the multistage NMPC approach yields much better accuracy across all tested frequencies. The simulations demonstrate that the proposed multistage NMPC approach can be solved for the 3-D trajectory tracking problem in real time.