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Performance Analysis of Switched Control Systems Under Common-source Digital Upsets Modeled by MDHMM

Author

Listed:
  • Rui Wang
  • Yanxiao Li
  • Hui Sun
  • Youmin Zhang
  • Yigang Sun

Abstract

This paper proposes the theoretical model to analyze the performance degradation of control systems subject to common-source digital upsets. In this paper, a multidimensional hidden Markov model (MDHMM) is used to characterize the correlated upsets and reveals the relationship between complex environments and stochastic random digital upsets injected into the control systems. These digital upsets coming from artificial complex environments are operated on distributed redundant processing controllers. Furthermore, this paper develops the theoretical analysis model for performance degradation of control systems under common-source digital interferences modeled by MDHMM. Theoretical estimations for different redundant configurations are analyzed. Then corresponding simulation verifications for a specific control system are also conducted in details and compared with the theoretical analysis results. These analyses can help to select an optimal redundant design and provide an example for control systems design. This analysis also helps to balance the performance of system, reliability of system, and costs of system design in applications.

Suggested Citation

  • Rui Wang & Yanxiao Li & Hui Sun & Youmin Zhang & Yigang Sun, 2018. "Performance Analysis of Switched Control Systems Under Common-source Digital Upsets Modeled by MDHMM," Complexity, Hindawi, vol. 2018, pages 1-12, November.
    • Handle: RePEc:hin:complx:4329053
    DOI: 10.1155/2018/4329053
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    1. Nebojša Malešević & Dimitrije Marković & Gunter Kanitz & Marco Controzzi & Christian Cipriani & Christian Antfolk, 2018. "Vector Autoregressive Hierarchical Hidden Markov Models for Extracting Finger Movements Using Multichannel Surface EMG Signals," Complexity, Hindawi, vol. 2018, pages 1-12, February.
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