引用本文: | 沈继红,张长斌,柴艳有,秦太白.递推批量MGM(1,N)模型在滑行艇运动姿态预报中的应用[J].哈尔滨工业大学学报,2010,42(7):1163.DOI:10.11918/j.issn.0367-6234.2010.07.034 |
| SHEN JI-hong,ZHANG Chang-bin,CHAI Yan-you,QIN Tai-bai.Application of recursive batch MGM(1,N) model in prediction of planing craft motion attitude[J].Journal of Harbin Institute of Technology,2010,42(7):1163.DOI:10.11918/j.issn.0367-6234.2010.07.034 |
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摘要: |
为了设计出有效的滑行艇的自动控制系统,需要建立预测模型对其运动姿态进行实时的、精确的预报.分析利用MGM(1,N)模型对滑行艇运动姿态进行预报的适用性.同时,针对滑行艇运动姿态数据的特点和预报的实时性要求,提出了新采集了一批数据之后,计算模型的参数矩阵的递推公式.利用该公式可以在提高预测精度、延长预测时间的同时,不会显著的增加计算量.数值仿真试验的结果表明,将批量递推MGM(1,N)模型应用于滑行运动姿态预报是可行的,并且具有非常高的预测精度. |
关键词: MGM(1 N)模型 批量递推 滑行艇 运动姿态 预报 |
DOI:10.11918/j.issn.0367-6234.2010.07.034 |
分类号:U674.942 |
基金项目:哈尔滨工程大学水下智能机器人技术国防科技重点实验室基金资助项目 |
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Application of recursive batch MGM(1,N) model in prediction of planing craft motion attitude |
SHEN JI-hong1, ZHANG Chang-bin2, CHAI Yan-you1, QIN Tai-bai3
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1.College of Science,Harbin Engineering University,Harbin 150001,China;2.College of Automation,Harbin Engineering University,Harbin 150001,China;3.College of Shipbuilding Engineering,Harbin Engineering University,Harbin 150001,China
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Abstract: |
To design an effective automatic control system of planing craft,a prediction model should be built to realize the real-time and precise prediction of its motion attitude.The applicability of using MGM(1,N) model to predict the planing motion attitude was analyzed.According to the characteristics of planing craft motion attitude data and real-time request of prediction,the recurrence formula was proposed to calculate MGM(1,N) model’s parameter matrix after a batch of data was acquired.Using this formula,the prediction accuracy can be greatly improved and the predicting time can be prolonged without the significant increase of computational complexity.The result of numerical simulation shows that it is feasible to use recursive batch MGM(1,N) model to predict the motion attitude of planing craft and the prediction accuracy is very high. |
Key words: MGM(1,N) model recursive batch planing craft motion attitude prediction |