面向多源干扰的动力定位船舶精细抗干扰控制
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作者单位:

1.武汉理工大学高性能舰船技术教育部重点实验室;2.武汉理工大学船海与能源动力工程学院;3.武汉理工大学船舶与能源动力工程学院;4.中国船舶及海洋工程设计研究院,喷水推进技术重点实验室

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中图分类号:

TP273

基金项目:

国家自然科学基金(项目批准号: 51879210, 51979210),中央高校基本科研业务费专项资金资助(项目批准号: 2019Ⅲ040, 2019III132CG)


Elegant anti-disturbance control of dynamic positioning in the presence of multi-source disturbance
Author:
Affiliation:

1.School of Naval Architecture,Ocean and Energy Power Engineering,Wuhan University of Technology;2.Key Laboratory of High Performance Ship Technology of Ministry of Education;3.Science and Technology on Water Jet Propulsion Laboratory

Fund Project:

The National Natural Science Foundation of China (51879210, 51979210),The Fundamental Research Funds for the Central Universities(2019Ⅲ040, 2019III132CG)

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    摘要:

    针对动力定位船舶非线性模型以及多源干扰导致的定位不精确问题,考虑不同干扰的特点及其在非线性模型中的响应特性提出了一种基于无源精细化扩张状态观测器的鲁棒自适应抗扰控制方法.首先,建立了动力定位船舶数学模型和多源干扰模型,并根据系统模型设计无源精细化扩张状态观测器实时估计船舶状态及所受的多源干扰;其次,在此基础上引入动态面控制技术,在控制律中设计了鲁棒自适应项以补偿估计误差;最后证明了该闭环级联系统所有误差信号一致最终有界.对一艘动力定位船舶进行了仿真实验,结果表明该方法在干扰估计和状态估计方面优于传统扩张状态观测器,验证了该控制方法的有效性.

    Abstract:

    Aiming at the problem of inaccurate positioning caused by nonlinear model and multi-source disturbance of dynamic positioning (DP) vessel model, a robust adaptive anti-disturbance control method based on passive elegant extended state observer (PEESO) was proposed, which takes into account the characteristics of different disturbances and their responses in the nonlinear model. Firstly, the DP vessel model and multi-source disturbance model were established, and a PEESO was designed to estimate the vessel states and multi-source disturbance in real time according to the system model. Secondly, based on the model and estimated values of vessel state and disturbance, the dynamic surface control technique was introduced and the robust adaptive term was designed in the control law to compensate the estimation error. Finally, it was proven that all error signals of the DP closed-loop cascade system are consistent and ultimately bounded. The simulation results showed that the method is superior to the traditional ESO in disturbance estimation and state estimation, which verifies the effectiveness of the proposed control method.

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  • 收稿日期:2021-10-20
  • 最后修改日期:2022-02-28
  • 录用日期:2022-03-15
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