使用统一抽样进行有效最小平方状态估计
1Electrical and Computer Engineering Department, Northeastern University, Boston, MA 02115 USA.
概括
这项研究引入了大型系统状态估计的新方法. 统一采样行近似统计杆分数,使得最小方程问题的有效解决方案.
科学领域:
- 控制系统工程
- 数字分析
- 计算数学
背景情况:
- 对于大规模,离散时间,线性时间不变系统的状态估计通常用最小平方问题来表达.
- 由于随着时间的推移,问题尺寸越来越大,因此出现了计算挑战.
- 随机抽样提供了近似结果,但需要计算统计杆分数,这很困难.
研究的目的:
- 提出一个替代的,可行的计算方法来近似统计杆得分.
- 能够有效地近似和解决大规模最小方程状态估计问题.
- 为拟议的近似方法提供理论保证.
主要方法:
- 通过统一的行抽样,开发一个近似统计杆分数的方法.
- 将这个近似应用于线性时间不变系统的最小平方状态估计问题.
- 分析统一抽样近似的理论保证.
主要成果:
- 统一的行采样为估计杆分数提供了足够弱的近似值.
- 拟议的方法可提供合理的杆得分.
- 这种近似方法适用于有效地解决最小平方值估计问题.
结论:
- 统一行采样为大规模状态估计中近似杆分数提供了一个实际的替代方案.
- 该方法简化了随机抽样技术的计算复杂性.
- 这项研究为线性系统状态估计提供了更有效和可扩展的解决方案.
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