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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2012  >  12(1): 38-44
MA Wei-jia, SHI Sheng-zhe, ZOU Jing, PANG Yong-jie, ZHU Kai. Extreme short-time prediction technology of high speed unmanned surface vehicle motion[J]. Journal of Traffic and Transportation Engineering, 2012, 12(1): 38-44. doi: 10.19818/j.cnki.1671-1637.2012.01.007
Citation: MA Wei-jia, SHI Sheng-zhe, ZOU Jing, PANG Yong-jie, ZHU Kai. Extreme short-time prediction technology of high speed unmanned surface vehicle motion[J]. Journal of Traffic and Transportation Engineering, 2012, 12(1): 38-44. doi: 10.19818/j.cnki.1671-1637.2012.01.007
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Extreme short-time prediction technology of high speed unmanned surface vehicle motion

doi: 10.19818/j.cnki.1671-1637.2012.01.007

  • School of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, Heilongjiang, China

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  • Author Bio:

    MA Wei-jia(1981-), male, doctoral student, +86-451-82589181, maweijia@sina.cn

    PANG Yong-jie(1955-), male, professor, +86-451-82588922, pangyongjie@hrbeu.edu.cn

  • Received Date: 2011-09-16
  • Publish Date: 2012-02-25
    Abstract
  • Multiple seasonal ARIMA(auto regressive integrated moving average) model based on time series was used, the extreme short-time prediction technology of unmanned surface vehicle motion was studied based on the seakeeping test data of boat model in regular wave.ARMA(auto regressive moving average) models with trend difference and seasonal difference were adopted, Akaike information criterion and white noise inspection method were carried out, and the chosen best model was validated.Extreme short-time prediction in twenty steps was made for unmanned surface vehicle.Calculation result indicates that the maximum errors are not more than 6% in the former ten-step predictions of acceleration, heave and pitch.With the increase of prediction step, the error has enlarging trend, the maximum error reaches to 16.68% in the following ten-step prediction of acceleration.So extreme short-time prediction technology is effective.

     

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