SIA OpenIR  > 海洋机器人卓越创新中心
基于预报建模的水面机器人运动控制方法研究
其他题名Research on Motion Control Method Based on Prediction Modeling for Unmanned Surface Vehicle
于金波1,2
导师胡志强
分类号TP242
关键词水面机器人 时间序列分析预报法 灰色预报法 滑模控制
索取号TP242/Y74/2017
页数61页
学位专业计算机应用技术
学位名称硕士
2017-05-24
学位授予单位中国科学院沈阳自动化研究所
学位授予地点沈阳
作者部门海洋机器人卓越创新中心
摘要水面机器人具有具有体积小、运动灵活、低成本、低消耗的特点,由于海洋空间环境危险、复杂,不适合人类生存,水面机器人可以代替有人航行系统完成水面环境监测、科学考察、灾难救援、国防安全等领域的一系列海洋任务。然而由于海面海况非常复杂,水面机器人在运动过程中需要面对未知的、动态的、存在时变扰动和噪声的外部环境,这通常导致机器人在水面的适航性和可操纵性严重下降,传统的机器人控制技术很难取得满意的控制效果,为了使水面机器人在各种海洋任务中能够发挥出更有效的作用,需要研究更有效的水面机器人运动控制技术。 论文内容分三部分展开: 第一部分,首先介绍了水面机器人的研发与应用情况,然后结合船舶运动控制方法详细介绍了水面机器人的运动控制方法,以及船舶运动姿态预报方法。之后介绍了水面机器人的坐标系以及三自由度数学模型,并在此基础上得到水面机器人适用的水平面运动数学模型。 第二部分,研究水面机器人运动姿态预报方法。介绍了时间序列分析预报法和灰色预报法,根据水面机器人在海洋中实航的姿态数据,通过仿真,对比AR模型和GM(1,1)模型对水面机器人运动时艏摇和纵摇的实时预报性能,得到了一种更适合于水面机器人运动姿态预报的方法。 第三部分,研究水面机器人的运动控制方法,阐述平行控制思想以及预报建模在水面机器人运动控制中的作用。根据水面机器人水平面运动方程,应用滑模控制理论建立水面机器人航向运动的滑模控制器,然后基于平行控制思想中人工系统的概念,结合水面机器人运动姿态预报,建立基于预报建模的滑模控制器。最后,在航向控制器设计的基础之上,结合水面机器人的航迹跟踪,采用滑模控制器和基于预报建模的滑模控制器分别对水面机器人的水平面运动进行仿真,结果表明,相同扰动的情况下,基于预报建模的滑模控制器对于水面机器人水平面运动的整体控制效果更优。
其他摘要Unmanned surface vehicle has the characteristics of small size, flexible movement, low cost and low consumption. As the marine space environment is dangerous, complex, not suitable for human survival, unmanned surface vehicle can replace a number of ocean missions in areas such as surface monitoring, scientific investigation, disaster relief, national defense and other areas of a series of marine tasks. However, due to the complex sea conditions, The unmanned surface vehicle in the process of movement need to face the unknown, dynamic, time-varying disturbance and noise external environment, which usually leads to the airworthiness and maneuverability of a serious decline of the unmanned surface vehicle. And the traditional robot control technology is difficult to achieve satisfactory control effect. In order to make the unmanned surface vehicle in a variety of marine tasks can play a more effective role, need to study more effective unmanned surface vehicle motion control method. The content of the paper is divided into three parts: In the first part, the development and application of the unmanned surface vehicle are introduced. Then, the motion control method of the unmanned surface vehicle are introduced in detail with the control method of the ship, and then introduce the method of ship motion attitude prediction. Then, the coordinate system of the unmanned surface vehicle and the three-degree-of-freedom mathematical model are introduced, and the mathematical model of the horizontal motion of the unmanned surface vehicle is obtained. In the second part, the paper focuses on the method of motion attitude prediction of the unmanned surface vehicle, expounds the parallel control idea and the role of prediction modeling in the motion control of unmanned surface vehicle, and introduces the time series analysis and prediction method and gray prediction method. According to the attitude data of the unmanned surface vehicle in the ocean, comparing the AR model and GM (1,1) model to forecast the heading and pitch of the unmanned surface vehicle movement, established the unmanned surface vehicle motion attitude prediction model. The third part is to study the motion control method of the unmanned surface vehicle. According to the horizontal plane motion equation of the unmanned surface vehicle, the sliding mode controller of the unmanned surface vehicle is established by using the sliding mode control theory. Based on the concept of artificial system in parallel control thought and the motion attitude prediction of the unmanned surface vehicle, a sliding mode controller based on forecast modeling is established. Finally, the simulation performance of the algorithm is verified by simulation. Based on the design of the heading controller and the tracking of the unmanned surface vehicle, the sliding mode controller and the sliding mode controller based on the prediction model are used to simulate the horizontal motion of the unmanned surface vehicle. The results show that the sliding mode controller based on prediction modeling has better control performance under the same disturbance.
语种中文
产权排序1
文献类型学位论文
条目标识符http://ir.sia.cn/handle/173321/20535
专题海洋机器人卓越创新中心
作者单位1.中国科学院沈阳自动化研究所
2.中国科学院大学
推荐引用方式
GB/T 7714
于金波. 基于预报建模的水面机器人运动控制方法研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2017.
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