动力定位系统自适应滤波技术  

Research on adaptive filtering techniques in dynamic positioning systems

作　　者：齐国鹏[1] 俞孟蕻[1] 袁伟[1] 

机构地区：[1]江苏科技大学计算机学院,江苏镇江212003

出　　处：《舰船科学技术》2013年第10期96-100,共5页Ship Science and Technology

基　　金：江苏省科技支撑计划项目资助(BE2011149)

摘　　要：与普通船舶相比,耙吸挖泥船变吃水作业动力定位的滤波器设计,不仅需要考虑到模型偏差,还需要考虑到模型的时变性和突变性。本文采用Sage-Husa自适应滤波和强跟踪卡尔曼滤波相结合的改进自适应滤波算法,前者滤波精度高但自适应能力有限,后者应对突变的能力较强但精度有限。由仿真实验可以看出,二者的有机结合很好地解决了耙吸挖泥船变吃水作业动力定位的滤波问题。Compared with ordinary ships, the filter design on trailing suction hopper dredger＇s dynamic positioning system under changing draft state, not only need to consider the model deviation, but also need to consider the model of time variation and mutation. In this paper, improved adaptive filtering algorithm, which combined Sage-Husa adaptive filtering with strong tracking Kalman filtering,the former has high filtering accuracy but its adaptive capacity is not satisfactory, the latter has strong ability dealing with mutations but its accuracy is low. Through the simulation, we can find that compared them together, the filter problem on trailing suction hopper dredger＇s dynamic positioning system under changing draft state could be solved successfully.

关 键 词：耙吸挖泥船 变吃水作业 动力定位 滤波器 改进的自适应滤波算法 

分 类 号：U615.351.2[交通运输工程—船舶及航道工程]