基于智能预测控制的鱼雷状小型无人艇轨迹跟踪研究

Trajectory tracking of small torpedo-type unmanned surface vessel based on intelligent predictive control

  • 摘要:
    目的 针对无人艇(USV)在狭窄湖泊、涵洞作业时存在精度保持难和航迹控制难的问题,以自主研制的一款鱼雷状小型USV为对象,提出一种轨迹跟踪智能预测控制方法。
    方法 首先,构建自主研制的欠驱动USV非线性状态空间模型;然后,设计智能预测控制器,该控制器基于模型预测控制的设计思想并结合改进的粒子群算法,在线决策、优化每一时刻的性能指标并纠正预测状态;最后,开展仿真和湖试试验测试系统对参考轨迹的跟踪性能,并与线性模型预测控制器的跟踪性能进行比较。
    结果 结果表明,所设计的智能预测控制器超调小、抗干扰性好。
    结论 所提方法不仅能运用于鱼雷状小型USV跟踪系统,也能对其他USV跟踪系统起到很好的借鉴作用。

     

    Abstract:
    Objective Aiming at the difficulties of the accuracy maintenance and tracking control of unmanned surface vessels (USVs) operating in narrow lakes and culverts, an intelligent predictive control method for trajectory tracking is proposed on the basis of a self-developed small torpedo-type USV.
    Methods First, a self-developed nonlinear state space model of the underactuated USV is constructed. An intelligent predictive controller is designed on the basis of the model predictive control design concept and combined with an improved particle swarm optimization (PSO) algorithm to make online decisions, optimize the performance indicators at every moment and correct the predicted state. Finally, simulation and lake tests are carried out to test the tracking performance of the system on reference trajectories, and the tracking performance is compared with that of the linear model predictive controller.
    Results The results show that the designed intelligent predictive controller has fast response speed, small overshoot and good anti-interference capabilities.
    Conclusion The proposed method can not only be applied to the tracking systems of small torpedo-type USVs, but can also provide references for other USV tracking systems.

     

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