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辅助模型非线性创新最小平方算法用于通过全尺度测试数据识别船舶4-DOF.
Chunyu Song1, Yinfu Li1, Jianghua Sui2
1Navigation and Ship Engineering College, Dalian Ocean University, Dalian, 116023, China.
这项研究引入了用于船舶系统识别的新算法,提高了模拟复杂船舶运动动态的准确性和效率. 该方法增强了数据利用,以实现更可靠的船舶智能导航工程.
科学领域:
- 海洋工程 海洋工程
- 控制系统 控制系统
- 系统识别系统识别系统
背景情况:
- 船舶运动建模面临的挑战是由于很大的惯性,合系统和不准确的数据.
- 现有的识别方法与未测量的船舶数据和规模效应扎.
研究的目的:
- 为准确的船舶系统识别提出一个改进的算法.
- 为了解决模拟复杂船舶动态和数据稀缺性的局限性.
主要方法:
- 开发了一个辅助模型非线性创新最小平方识别算法.
- 利用辅助模型输出来取代船舶测试数据中的不可测量的变量.
- 使用触点函数优化错误,以提高准确性.
主要成果:
- 改进的算法证明了随着时间的推移不断接近零的误差减少.
- 与现有方法相比,实现了显著提高的识别准确性和融合效率.
- 验证了算法的可靠性用于实际应用.
结论:
- 拟议的识别方法为船舶系统建模提供了卓越的准确性和效率.
- 这种技术适用于先进的船舶智能导航工程.
- 该算法有效地克服了与不完整和不准确的船舶数据相关的挑战.
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