对于具有异质传感器的非线性系统的有限时间稳健分布式估计
IEEE transactions on cybernetics
|October 22, 2024
概括
本研究介绍了一个有限时间分布式状态估计算法,用于具有多种传感器的非线性系统. 该方法通过三阶段方法确保准确的状态估计,提高系统性能.
科学领域:
- 控制系统工程 控制系统工程
- 信号处理 信号处理
- 非线性动力学是一种非线性动力学.
背景情况:
- 分布状态估计对于具有多个传感器的网络系统至关重要.
- 在非线性系统中处理异质传感器存在重大挑战.
- 现有的方法经常在有限时间的融合和数据融合方面扎.
研究的目的:
- 为离散时间随机非线性系统开发有限时间分布状态估计 (DSE) 算法.
- 为了解决网络中异质传感器所带来的复杂性.
- 为了在有限的时间框架内确保准确和可靠的状态估计.
主要方法:
- 一个三个阶段的框架:先验预测,测量更新和共识融合.
- 交互式多重模型 (IMM) 用于准确的先验状态预测.
- 一种使用测量概率矩阵的新型异质测量信息融合算法.
- 基于共识的融合与共识权重用于分布式状态估计.
主要成果:
- 拟议的DSE算法实现了有限时间的融合.
- 对于具有异质传感器的非线性系统,证明了准确的状态估计.
- 通过模拟示例验证了算法的性能.
结论:
- 开发的有限时间DSE算法有效地处理具有异质传感器的非线性系统.
- 三阶段框架确保了准确的状态估计和有限时间的融合.
- 新的融合算法增强了各种传感器测量的利用.
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