带丢包和量化的参数不确定系统滚动时域估计

doi:10.3969/j.issn.1001-506X.2020.04.23

系统工程与电子技术 ›› 2020, Vol. 42 ›› Issue (4): 912-918.doi: 10.3969/j.issn.1001-506X.2020.04.23

带丢包和量化的参数不确定系统滚动时域估计

刘帅¹(), 赵国荣¹(), 曾宾²(), 高超¹()

1. 海军航空大学岸防兵学院, 山东烟台 264001
2. 中国人民解放军92095部队, 浙江台州 318000

收稿日期:2019-09-18 出版日期:2020-03-28 发布日期:2020-03-28
作者简介:刘帅(1990-),男,博士研究生,主要研究方向为组网导航技术。E-mail:15165714808@163.com|赵国荣(1964-),男，教授，博士研究生导师，博士，主要研究方向为飞行器导航与控制。E-mail:GRZhao6881@163.com|曾宾(1989-),男,博士研究生,主要研究方向为组网导航技术。E-mail:363929893@qq.com|高超(1985-),男,工程师,博士,主要研究方向为组网导航技术。E-mail:gaochao.shd@163.com
基金资助:
国家自然科学基金(61473306);国家自然科学基金(61903374)

Moving horizon estimation for uncertain systems with packet dropouts and quantization

Shuai LIU¹(), Guorong ZHAO¹(), Bin ZENG²(), Chao GAO¹()

1. Coastal Defence Academy, Naval Aviation University, Yantai 264001, China
2. Unit 92095 of the PLA, Taizhou 318000, China

Received:2019-09-18 Online:2020-03-28 Published:2020-03-28
Supported by:
国家自然科学基金(61473306);国家自然科学基金(61903374)

摘要/Abstract

摘要：

针对网络化系统中丢包、量化和参数不确定性对状态估计的影响,提出一种带有预测补偿机制的鲁棒滚动时域估计算法。将丢包现象描述为概率已知的随机Bernoulli序列,并利用丢失数据的预测值进行丢包补偿,将数据量化引入的量化误差描述为观测方程中的一个有界不确定参数,将模型的不确定性描述为系统矩阵受到随机扰动,基于滚动优化策略,考虑量化和模型不确定性影响最严重的情况,通过滚动求解一个min-max问题得到最优状态估计器。对所提算法进行稳定性分析,推导了估计误差范数平方期望的一个上界函数,给出了估计误差范数平方期望收敛的充分条件。最后,通过仿真验证了所提算法的有效性。

关键词: 滚动时域估计, 预测补偿, 数据量化, 模型不确定性, min-max问题, 稳定性分析

Abstract:

To solve the constraints of packet dropouts, quantization and model uncertainty in networked systems for state estimation, a robust moving horizon estimation (MHE) algorithm with prediction compensation is proposed. A group of Bernoulli distributed random variables is employed to describe the phenomenon of packet dropouts and the predictor of the missing measurements is applied as a compensator, the error introduced by data quantization is described as a bounded uncertainty parameter in the observation equation, the uncertainty of the model is described by stochastic parameter perturbations in the system matrix, based on the moving horizon strategy, and considering the worst-case caused by quantization and model uncertainty, the optimal state estimation is obtained by solving a min-max problem. The stability of the proposed algorithm is studied, explicit bounding sequence on the expectation of the square norm of estimation error is obtained, and a sufficient condition for the convergence of the square norm of estimation error is given. Finally, an example is given to demonstrate the efficiency of the proposed method.

Key words: moving horizon estimation (MHE), prediction compensation, quantization, model uncertainty, min-max problem, stability analysis

中图分类号:

TP271.7

刘帅, 赵国荣, 曾宾, 高超. 带丢包和量化的参数不确定系统滚动时域估计[J]. 系统工程与电子技术, 2020, 42(4): 912-918.

Shuai LIU, Guorong ZHAO, Bin ZENG, Chao GAO. Moving horizon estimation for uncertain systems with packet dropouts and quantization[J]. Systems Engineering and Electronics, 2020, 42(4): 912-918.

图/表 5

参考文献 23

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带丢包和量化的参数不确定系统滚动时域估计

Moving horizon estimation for uncertain systems with packet dropouts and quantization

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