ZSM-IMM和ZPRM-IMM:两种基于多个模型的新型交互状态估计算法,用于未知但有界噪声下的随机切换系统
Zi-Yun Wang1, Yue Wang1, Yan Wang1
1Engineering Research Center of Internet of Things Technology and Applications (Ministry of Education), Jiangnan University, Wuxi, Jiangsu 214122, China.
ISA transactions
|May 16, 2025
概括
两种新的状态估计算法使用交互多重模型 (IMM) 技术提高了使用随机切换线性系统的准确性. 这些方法,包括zonotopic段最小化和P半径最小化,增强系统的识别和控制.
科学领域:
- 控制系统工程 控制系统工程
- 信号处理 信号处理
- 应用数学 应用数学 应用数学
背景情况:
- 随机交换线性系统在准确的状态估计中存在挑战,原因是系统动态的突然变化.
- 现有的多个模型算法可能会在系统不确定性下对状态估计保持严格的界限.
研究的目的:
- 为随机交换线性系统开发新的状态估计算法.
- 为了提高在不确定的环境中交互多个模型 (IMM) 算法的性能.
主要方法:
- 使用分段最小化推导一个zonotopic过器.
- 基于最小化区域段的IMM算法的建议,该算法有四个不同的步骤.
- 开发基于最小化P半径的zonotopicIMM算法,将其制定为线性矩阵不等式问题.
主要成果:
- 拟议的区域位段最小化IMM算法证明了有效的状态估计.
- 区位点P半径最小化IMM算法解决了区位点绑定的包装问题.
- 这两种算法都通过数值模拟和对Buck-Boost电路的实验分析来验证.
结论:
- 基于IMM的新算法为随机交换线性系统提供了改进的状态估计.
- 采用P半径最小化方法,可以有效地处理区域位状态估计中的不确定性.
- 经过验证的算法在现实世界的系统中显示了实际的应用性,比如动力电子转换器.
关键词:
IMMM IMM IMM IMM IMM IMM IMM IMM IMM IMM IMM IMM IMM IMM IMM IMM IMM IMM IMM线性随机切换系统 线性随机切换系统区域图形 - 半径最小化区域拓展区段最小化方法更多相关视频
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