基于隐马尔可夫模型的切换飞行控制系统性能分析

王蕊; 李彦骁; 孙辉; 陈增强

doi:10.11999/JEIT160492

基于隐马尔可夫模型的切换飞行控制系统性能分析

doi: 10.11999/JEIT160492

1.
(中国民航大学电子信息与自动化学院天津 300300) ②(南开大学计算机与控制工程学院天津 300071)

基金项目:

国家自然科学基金(61403395, U1533201)，中国民航大学中央高校基本科研业务费(3122014C024)，中国教育部留学回国人员科研启动基金，民航局科技创新引导基金(20150227)

计量
- 文章访问数: 1315
- HTML全文浏览量: 188
- PDF下载量: 414
- 被引次数: 0
出版历程
- 收稿日期: 2016-05-16
- 修回日期: 2016-10-25
- 刊出日期: 2017-04-19

Performance Analysis of Switched Flight Control Systems Based on Hidden Markov Model

1.
(College of Information Engineering and Automation, Civil Aviation University of China, Tianjin 300300, China)
2.
(Computer and Control Engineering College, Nankai University, Tianjin 300071, China)

Funds:

The National Natural Science Foundation of China (61403395, U1533201), The Fundamental Research Funds for the Central Universities of CAUC (3122014D024), The Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry, Science and Technology Innovation Guidance Funds of CAAC (20150227)

摘要

摘要: 该文研究了一种由电磁环境对电子设备产生的数字干扰来驱动的切换飞行控制系统性能分析模型。其中，从电磁干扰的产生原理角度，采用隐马尔可夫模型(Hidden Markov Model, HMM)描述数字电磁干扰特性并对其进行建模分析，同时针对HMM参数训练算法存在对初值选择敏感的问题，提出一种快速的初值选择策略，可以在经典Baum-Welch算法迭代下达到指定的收敛精度。最后将HMM电磁干扰注入分布式飞行控制系统性能观测平台，从理论与仿真的角度对比了不同电磁环境下分布式飞行控制系统的性能下降情况。仿真实验表明：与已有的数字电磁干扰建模分析方法相比，HMM具有更高的准确度，并且仿真所得性能下降程度与理论分析一致
- 飞行控制系统 /
- 隐马尔可夫模型 /
- 稳定性 /
- 数字干扰 /
- 切换系统
Abstract: This paper proposes the performance analysis model of switched flight control systems driven by the digital upsets when electronics devices are subject to electromagnetic environments. Hidden Markov Model (HMM) is used to describe the characteristics of digital upsets and construct the model based on the theory of the electromagnetic interferences. The parameter estimation algorithms of the traditional training method for HMM are sensitive to initial parameters, therefore, this paper proposes a fast initial parameter selection strategy which can also accelerate the training processes. At the end, HMM-based electromagnetic interferences are fed to the performance observation platform for the distributed flight control systems. This paper also compares multiple performance degradation results under different electromagnetic fields from theory and simulation perspectives. Simulation results demonstrate HMM model can characterize the digital electromagnetic upsets more accurately compared to the existed digital electromagnetic models, and simulation results of the corresponding performance degradation are consistent with the theoretic results.
- Flight control systems /
- Hidden Markov Model (HMM) /
- Stability /
- Digital upsets /
- Switched systems

HTML全文

参考文献(12)

BELCASTRO C M. Closed-loop HIRF experiments performed on a fault tolerant flight control computer[C]. 16th Digital Avionics Systems Conference, Irvine, USA, 1997: 4.1-40-54.

SHOOMAN M L. A study of occurrence rates of electromagnetic interference (EMI) to aircraft with a focus on HIRF (external) high intensity radiated fields[R]. NASA Technical Report CR-194895, 1994.

Wang R, GRAY W S, GONZALEZ O R, et al. Tracking performance of distributed recoverable flight control systems subject to high intensity radiated fields[J]. IEEE Transactions on Aerospace and Electronic Systems, 2013, 49(1): 521-542. doi: 10.1109/TAES.2013.6404118.

Wang R, Sun H, and Ma Z Y. Stability and performance analysis of a jump linear control system subject to digital upsets[J]. Chinese Physics B, 2015, 24(4): 6-15. doi: 10.1088/ 1674-1056/24/4/040201.

GAYATHRI P and AYYAPPAN S. Off-line handwritten character recognition using hidden Markov model[C]. International Conference on Advances in Computing, Communications and Informatics (ICACCI), New Delhi, India, 2014: 518-523.

SOUALHI A, CLERC G, RAZIK H, et al. Hidden Markov models for the prediction of impending faults[J]. IEEE Transactions on Industrial Electronics, 2016, 63(5): 3271-3281. doi: 10.1109/TIE.2016.2535111.

HE Q and BAO C C. A gain-adaptive parallel HMM for speech enhancement[C]. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, Hong Kong, China, 2015: 35-42.

Ge Y, CHEN Q, and JIANG M. Stability of networked control systems based on hidden Markov models[C]. 7th World Congress on Intelligent Control and Automation, Chongqing, China, 2008: 5453-5456.

LU Jinhu and CHEN Guanrong. A time-varying complex dynamical network model and its controlled synchronization criteria[J]. IEEE Transactions on Automatic Control, 2005, 50(6): 841-846. doi: 10.1109/TAC.2005.849233.

China Civil Aviation Regulations-25-R4[R]. Airworthiness Standards for Transport Aircraft, 2011.

HUANG Qingqing, G E Rong, KAKADE Sham, et al. Minimal realization problems for hidden Markov models[J]. IEEE Transactions on Signal Processing, 2016, 64(7): 1896-1904. doi: 10.1109/TSP.2015.2510969.

RABINER L R. A tutorial on hidden Markov models and selected applications in speech recoginiton[J]. Proceedings of the IEEE, 1989, 77(2): 257-286.

施引文献

资源附件(0)

访问统计