余荣臻, 袁剑平, 李俊益. 基于蝗虫优化算法的大型运输船舶自适应控制[J]. 中国舰船研究, 2023, 18(3): 66–74. doi: 10.19693/j.issn.1673-3185.02782
引用本文: 余荣臻, 袁剑平, 李俊益. 基于蝗虫优化算法的大型运输船舶自适应控制[J]. 中国舰船研究, 2023, 18(3): 66–74. doi: 10.19693/j.issn.1673-3185.02782
YU R Z, YUAN J P, LI J Y. Adaptive control of large transport ship based on grasshopper optimization algorithm[J]. Chinese Journal of Ship Research, 2023, 18(3): 66–74. doi: 10.19693/j.issn.1673-3185.02782
Citation: YU R Z, YUAN J P, LI J Y. Adaptive control of large transport ship based on grasshopper optimization algorithm[J]. Chinese Journal of Ship Research, 2023, 18(3): 66–74. doi: 10.19693/j.issn.1673-3185.02782

基于蝗虫优化算法的大型运输船舶自适应控制

Adaptive control of large transport ship based on grasshopper optimization algorithm

  • 摘要:
      目的  海上航行环境随机复杂多变,而智能自主航行是大型远洋运输船舶发展的重要趋势,为此,提出一种新的自适应控制方法。
      方法  首先,基于蝗虫优化算法(GOA),将线性二次型调节器(LQR)控制方法与一阶动态积分滑模控制方法相融合;然后,结合实时监测波浪干扰力的非线性无源估计器,将船舶高、低频运动信号进行分离;最后,与LQR控制方法和一阶动态积分滑模控制方法进行仿真对比。
      结果  结果显示,新的控制方法具有更好的瞬态和稳态跟踪性能,在不同的海况下能够克服随机波浪的影响,具有较强的鲁棒性。
      结论  新的控制方法具有复杂环境下的自适应调节能力,且控制响应快、精度高、无效操舵少,能极大地提高大型运输船舶的航行效率、安全性和稳定性。

     

    Abstract:
      Objectives  The maritime navigation environment is random, complex and changeable, and intelligent autonomous navigation is an important trend in the development of large ocean-going transport ships, for which a new adaptive control method is proposed.
      Methods  First, the linear quadratic regulator (LQR) control method is integrated with the first-order dynamic integral sliding mode control method based on the grasshopper optimization algorithm (GOA). A nonlinear passive estimator with real-time monitoring of wave disturbance forces is then combined to separate the high and low-frequency motion signals of the ship. Finally, the simulation results of the proposed method are compared with those of the LQR control method and first-order dynamic integral sliding mode control method.
      Results  The results show that the new control method has better transient and steady-state tracking performance, and is able to overcome the effects of random waves under different sea conditions with strong robustness.
      Conclusions  The new control method has such abilities as self-adjustment in complex environments, fast control response, high precision and less redundant steering, enabling it to greatly improve the navigation efficiency, safety and stability of large transport ships.

     

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