基于预测控制的水下自航器抗海浪变深控制分析  被引量:3

Anti-wave Depth Control Analysis of Underwater Self-propelled Vehicle Based on Predictive Control

在线阅读下载全文

作  者:高国章[1] 李修宇 GAO Guozhang;LI Xiuyu(Energy and Power Engineering College,Wuhan University of Technology,Wuhan 430063,China)

机构地区:[1]武汉理工大学能源与动力工程学院,武汉430063

出  处:《船舶工程》2020年第6期91-97,共7页Ship Engineering

基  金:船舶动力工程技术交通运输行业重点实验室开发基金项目(KLMPET2018-2);中央高校基本科研业务费专项资金(2019Ⅲ046GX)。

摘  要:水下自主航行器在近水面航行中存在着深度跟踪和姿态控制较为困难的问题。为此,首先建立了自主航行器的近水面三自由度运动数学模型,然后设计了无迹卡尔曼滤波器实现对系统状态的估计;接着,利用斯特林内插法在变动的工作点处对自主航行器模型进行近似线性化,并根据线性化后的模型设计预测控制器,实现自主航行器的变深运动控制。经过仿真试验,验证了滤波器对自主航行器近水面运动状态估计的准确性以及预测控制器在抗海浪扰动上的控制效果。仿真结果表明,带有无迹卡尔曼滤波器的预测控制器可以快速、准确地实现自主航行器的深度跟踪控制与姿态控制,且具有响应速度快,对外部扰动鲁棒性强的特点。Underwater autonomous vehicles have problems in deep tracking and attitude control in nearsurface navigation.For the purpose,firstly the mathematical model of the near-surface three-degree-of-freedom motion of the autonomous vehicle is established,and then the unscented Kalman filter is designed to estimate the state of the system.Then,the Stirling interpolation method is used at the changing working point.The autonomous vehicle model is approximated linearly,and the predictive controller is designed according to the linearized model to realize the deepening motion control of the autonomous vehicle.Through simulation experiments,the accuracy of the filter’s estimation of the near-surface motion state of the autonomous vehicle and the control effect of the predictive controller on the anti-wave disturbance are verified.The simulation results show that the predictive controller with unscented Kalman filter can quickly and accurately realize the deep tracking control and attitude control of the autonomous vehicle,and has the characteristics of fast response and strong robustness to external disturbances.

关 键 词:水下自航器 近水面 无迹卡尔曼滤波 斯特林插值 模型预测控制 

分 类 号:U661.43[交通运输工程—船舶及航道工程]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象