基于隱馬爾可夫模型的切換飛行控制系統(tǒng)性能分析
doi: 10.11999/JEIT160492 cstr: 32379.14.JEIT160492
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1.
(中國民航大學電子信息與自動化學院 天津 300300) ②(南開大學計算機與控制工程學院 天津 300071)
國家自然科學基金(61403395, U1533201),中國民航大學中央高校基本科研業(yè)務費(3122014C024),中國教育部留學回國人員科研啟動基金,民航局科技創(chuàng)新引導基金(20150227)
Performance Analysis of Switched Flight Control Systems Based on Hidden Markov Model
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1.
(College of Information Engineering and Automation, Civil Aviation University of China, Tianjin 300300, China)
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2.
(Computer and Control Engineering College, Nankai University, Tianjin 300071, China)
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)
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摘要: 該文研究了一種由電磁環(huán)境對電子設備產(chǎn)生的數(shù)字干擾來驅動的切換飛行控制系統(tǒng)性能分析模型。其中,從電磁干擾的產(chǎn)生原理角度,采用隱馬爾可夫模型(Hidden Markov Model, HMM)描述數(shù)字電磁干擾特性并對其進行建模分析,同時針對HMM參數(shù)訓練算法存在對初值選擇敏感的問題,提出一種快速的初值選擇策略,可以在經(jīng)典Baum-Welch算法迭代下達到指定的收斂精度。最后將HMM電磁干擾注入分布式飛行控制系統(tǒng)性能觀測平臺,從理論與仿真的角度對比了不同電磁環(huán)境下分布式飛行控制系統(tǒng)的性能下降情況。仿真實驗表明:與已有的數(shù)字電磁干擾建模分析方法相比,HMM具有更高的準確度,并且仿真所得性能下降程度與理論分析一致
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關鍵詞:
- 飛行控制系統(tǒng) /
- 隱馬爾可夫模型 /
- 穩(wěn)定性 /
- 數(shù)字干擾 /
- 切換系統(tǒng)
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.-
Key words:
- Flight control systems /
- Hidden Markov Model (HMM) /
- Stability /
- Digital upsets /
- Switched systems
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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. -
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