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Performance Analysis of Switched Flight Control Systems Based on Hidden Markov Model |
WANG Rui① LI Yanxiao① SUN Hui① CHEN Zengqiang② |
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) |
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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.
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Received: 16 May 2016
Published: 20 December 2016
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Fund: 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) |
Corresponding Authors:
WANG Rui
E-mail: wrhappyfuture@hotmail.com
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[1] |
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.
|
[2] |
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.
|
[3] |
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.
|
[4] |
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.
|
[5] |
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.
|
[6] |
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.
|
[7] |
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.
|
[8] |
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.
|
[9] |
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.
|
[10] |
China Civil Aviation Regulations-25-R4[R]. Airworthiness Standards for Transport Aircraft, 2011.
|
[11] |
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.
|
[12] |
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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