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Optimal joint inspection and mission abort policy for a partially observable system

Author

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  • Cheng, Guoqing
  • Li, Ling
  • Shangguan, Chunxia
  • Yang, Nan
  • Jiang, Bo
  • Tao, Ningrong

Abstract

his paper presents a joint optimization of inspection and condition-based mission abort policy for a partially observable safety-critical system. The system deterioration is modeled by a hidden continuous-time Markov process. Condition monitoring can only reveal partial information about the hidden state of the system. A joint inspection and mission abort policy is developed by using multi-variate Bayesian control approach. The posterior probability of the system being in warning state is updated at each inspection by Bayes’ rule. The mission is aborted and the rescue procedure is initiated once the posterior probability exceeds the control limit. The problem is formulated and solved within the framework of Markov decision process which aims to minimize the expected total cost including inspection, mission failure and system failure cost. Some structural properties of the control limit are presented. Finally, numerical examples are provided to demonstrate the model.

Suggested Citation

  • Cheng, Guoqing & Li, Ling & Shangguan, Chunxia & Yang, Nan & Jiang, Bo & Tao, Ningrong, 2023. "Optimal joint inspection and mission abort policy for a partially observable system," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    • Handle: RePEc:eee:reensy:v:229:y:2023:i:c:s0951832022004872
    DOI: 10.1016/j.ress.2022.108870
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    References listed on IDEAS

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    Citations

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    Cited by:

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    2. Wang, Weikai & Chen, Xian, 2023. "Piecewise deterministic Markov process for condition-based imperfect maintenance models," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    3. Cheng, Guoqing & Shen, Jiayi & Wang, Fang & Li, Ling & Yang, Nan, 2024. "Optimal mission abort policy for a multi-component system with failure interaction," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    4. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2024. "Multi-attempt missions with multiple rescue options," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    5. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2023. "Optimal task sequencing and aborting in multi-attempt multi-task missions with a limited number of attempts," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    6. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2024. "A new self-adaptive mission aborting policy for systems operating in uncertain random shock environment," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    7. Zhao, Xian & Wang, Xinlei & Dai, Ying & Qiu, Qingan, 2024. "Joint optimization of loading, mission abort and rescue site selection policies for UAV," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    8. Meng, Sa & Xing, Liudong & Levitin, Gregory, 2024. "Optimizing component activation and operation aborting in missions with consecutive attempts and common abort command," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    9. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2024. "Optimal task aborting and sequencing in time constrained multi-task multi-attempt missions," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    10. Gámiz, M.L. & Navas-Gómez, F. & Raya-Miranda, R. & Segovia-García, M.C., 2023. "Dynamic reliability and sensitivity analysis based on HMM models with Markovian signal process," Reliability Engineering and System Safety, Elsevier, vol. 239(C).

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