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Fault detectability of Boolean control networks via nonaugmented methods

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Abstract

This study is concerned with the fault detectability of Boolean control networks (BCNs) by two nonaugmented methods. Firstly, the equivalent system-based approach is considered, and the equivalence of BCNs is applied to analyze weak active fault detectability. Further, an iterative matrix set-based approach is proposed, by which, several novel criteria for strong and weak active fault detectability are presented. Meanwhile, effective algorithms are designed to check strong and weak active fault detectability and generate all feasible input sequences with the minimum length. In comparison, our results reduce the computational complexity dramatically than the existing studies.

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References

  1. Kauffman S A. Metabolic stability and epigenesis in randomly constructed genetic nets. J Theor Biol, 1969, 22: 437–467

    Article  MathSciNet  Google Scholar 

  2. Glass L, Kauffman S A. The logical analysis of continuous, non-linear biochemical control networks. J Theor Biol, 1973, 39: 103–129

    Article  Google Scholar 

  3. Ideker T, Galitski T, Hood L. A new approach to decoding life: systems biology. Annu Rev Genom Hum Genet, 2001, 2: 343–372

    Article  Google Scholar 

  4. Kauffman S, Peterson C, Samuelsson B, et al. Random Boolean network models and the yeast transcriptional network. Proc Natl Acad Sci USA, 2003, 100: 14796–14799

    Article  Google Scholar 

  5. Saez-Rodriguez J, Simeoni L, Lindquist J A, et al. A logical model provides insights into T cell receptor signaling. Plos Comput Biol, 2007, 3: e163

    Article  MathSciNet  Google Scholar 

  6. Veliz-Cuba A, Kumar A, Josić K. Piecewise linear and Boolean models of chemical reaction networks. Bull Math Biol, 2014, 76: 2945–2984

    Article  MathSciNet  MATH  Google Scholar 

  7. Cheng D Z. Semi-tensor product of matrices and its application to Morgen’s problem. Sci China Ser F-Inf Sci, 2001, 44: 195–212

    Article  MathSciNet  MATH  Google Scholar 

  8. Li H T, Zhao G D, Meng M, et al. A survey on applications of semi-tensor product method in engineering. Sci China Inf Sci, 2018, 61: 010202

    Article  MathSciNet  Google Scholar 

  9. Yan Y Y, Cheng D Z, Feng J-E, et al. Survey on applications of algebraic state space theory of logical systems to finite state machines. Sci China Inf Sci, 2023, 66: 111201

    Article  MathSciNet  Google Scholar 

  10. Weiss E, Margaliot M, Even G. Minimal controllability of conjunctive Boolean networks is NP-complete. Automatica, 2018, 92: 56–62

    Article  MathSciNet  MATH  Google Scholar 

  11. Zhou R P, Guo Y Q, Liu X Z, et al. Stabilization of Boolean control networks with state-triggered impulses. Sci China Inf Sci, 2022, 65: 132202

    Article  MathSciNet  Google Scholar 

  12. Zhong J, Ho D W C, Lu J. A new approach to pinning control of Boolean networks. IEEE Trans Control Netw Syst, 2021, 9: 415–426

    Article  MathSciNet  Google Scholar 

  13. Zhang K, Zhang L, Su R. A weighted pair graph representation for reconstructibility of Boolean control networks. SIAM J Control Optim, 2016, 54: 3040–3060

    Article  MathSciNet  MATH  Google Scholar 

  14. Yu Y, Meng M, Feng J, et al. Observability criteria for Boolean networks. IEEE Trans Automat Contr, 2021, 67: 6248–6254

    Article  MathSciNet  MATH  Google Scholar 

  15. Liu Y, Zhong J, Ho D W C, et al. Minimal observability of Boolean networks. Sci China Inf Sci, 2022, 65: 152203

    Article  MathSciNet  Google Scholar 

  16. Wu Y, Sun X M, Zhao X, et al. Optimal control of Boolean control networks with average cost: a policy iteration approach. Automatica, 2019, 100: 378–387

    Article  MathSciNet  MATH  Google Scholar 

  17. Yao Y, Sun J. Optimal control of multi-task Boolean control networks via temporal logic. Syst Control Lett, 2021, 156: 105007

    Article  MathSciNet  MATH  Google Scholar 

  18. Wu Y H, Zhang J Y, Shen T L. A logical network approximation to optimal control on a continuous domain and its application to HEV control. Sci China Inf Sci, 2022, 65: 212203

    Article  MathSciNet  Google Scholar 

  19. Martincorena I, Campbell P J. Somatic mutation in cancer and normal cells. Science, 2015, 349: 1483–1489

    Article  Google Scholar 

  20. Layek R, Datta A. Fault detection and intervention in biological feedback networks. J Biol Syst, 2012, 20: 441–453

    Article  MathSciNet  Google Scholar 

  21. Sridharan S, Layek R, Datta A, et al. Boolean modeling and fault diagnosis in oxidative stress response. BMC Genomics, 2012, 13: S4

    Article  Google Scholar 

  22. Deshpande A, Layek R K. Fault detection and therapeutic intervention in gene regulatory networks using SAT solvers. Biosystems, 2019, 179: 55–62

    Article  Google Scholar 

  23. Fornasini E, Valcher M E. Fault detection of Boolean control networks. In: Proceedings of the 53rd IEEE Conference on Decision and Control, Los Angeles, 2014. 6542–6547

  24. Fornasini E, Valcher M E. Fault detection analysis of Boolean control networks. IEEE Trans Automat Contr, 2015, 60: 2734–2739

    Article  MathSciNet  MATH  Google Scholar 

  25. Leifeld T, Zhang Z, Zhang P. Fault detection for probabilistic Boolean networks. In: Proceedings of European Control Conference (ECC), Aalborg, 2016. 740–745

  26. Fornasini E, Valcher M E. Fault detection problems for Boolean networks and Boolean control networks. In: Proceedings of the 34th Chinese Control Conference (CCC), Hangzhou, 2015. 1–8

  27. Zhang Z, Leifeld T, Zhang P. Active fault detection of Boolean control networks. In: Proceedings of Annual American Control Conference (ACC), Milwaukee, 2018. 5001–5006

  28. Dou W, Zhao G, Li H, et al. Off-line fault detection of logical control networks. Int J Syst Sci, 2022, 53: 478–487

    Article  MathSciNet  MATH  Google Scholar 

  29. Zhao R, Feng J, Wang B. Passive-active fault detection of Boolean control networks. J Franklin Institute, 2022, 359: 7196–7218

    Article  MathSciNet  MATH  Google Scholar 

  30. Chen Z, Zhou Y, Zhang Z, et al. Semi-tensor product of matrices approach to the problem of fault detection for discrete event systems (DESs). IEEE Trans Circuits Syst II, 2020, 67: 3098–3102

    Google Scholar 

  31. Dong Z. Boolean network-based sensor selection with application to the fault diagnosis of a nuclear plant. Energies, 2017, 10: 2125

    Article  Google Scholar 

  32. Dong Z, Pan Y, Huang X. Parameter identifiability of Boolean networks with application to fault diagnosis of nuclear plants. Nucl Eng Tech, 2018, 50: 599–605

    Article  Google Scholar 

  33. Li H, Wang Y. Boolean derivative calculation with application to fault detection of combinational circuits via the semi-tensor product method. Automatica, 2012, 48: 688–693

    Article  MathSciNet  MATH  Google Scholar 

  34. Liu Z, Wang Y, Li H. New approach to derivative calculation of multi-valued logical functions with application to fault detection of digital circuits. IET Control Theor Appl, 2014, 8: 554–560

    Article  MathSciNet  Google Scholar 

  35. Cheng D, Qi H, Liu T, et al. A note on observability of Boolean control networks. Syst Control Lett, 2016, 87: 76–82

    Article  MathSciNet  MATH  Google Scholar 

  36. Cheng D, Qi H. Controllability and observability of Boolean control networks. Automatica, 2009, 45: 1659–1667

    Article  MathSciNet  MATH  Google Scholar 

  37. Cheng D, Li Z, Qi H. Realization of Boolean control networks. Automatica, 2010, 46: 62–69

    Article  MathSciNet  MATH  Google Scholar 

  38. Moore E F. Gedanken-experiments on sequential machines. Autom Studies, 1956, 34: 129–153

    MathSciNet  Google Scholar 

  39. Li Y, Li H. Fault isolation of logical control networks via set controllability of augmented system. IEEE Trans Circuits Syst II, 2023, 70: 1029–1033

    Google Scholar 

  40. Zhu S, Lu J, Azuma S, et al. Strong structural controllability of Boolean networks: polynomial-time criteria, minimal node control, and distributed pinning strategies. IEEE Trans Automat Contr, 2023, 68: 5461–5476

    Article  MathSciNet  MATH  Google Scholar 

  41. Zhu S, Lu J, Sun L, et al. Distributed pinning set stabilization of large-scale Boolean networks. IEEE Trans Automat Contr, 2023, 68: 1886–1893

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos. 62273201, 62203264), Research Fund for the Taishan Scholar Project of Shandong Province of China (Grant No. TSTP20221103), and Natural Science Fund of Shandong Province (Grant No. ZR2022QF061).

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Authors and Affiliations

  1. School of Mathematics, Shandong University, Jinan, 250100, China

    Rong Zhao, Caixia Wang, Yongyuan Yu & Jun-E. Feng

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  1. Rong Zhao
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  2. Caixia Wang
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  3. Yongyuan Yu
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  4. Jun-E. Feng
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Correspondence to Yongyuan Yu.

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Zhao, R., Wang, C., Yu, Y. et al. Fault detectability of Boolean control networks via nonaugmented methods. Sci. China Inf. Sci. 66, 222205 (2023). https://doi.org/10.1007/s11432-023-3787-y

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  • DOI: https://doi.org/10.1007/s11432-023-3787-y

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