Finite-time observability of probabilistic Boolean multiplex control networks
Yuxin Cui; Shu Li; Yunxiao Shan
Kybernetika (2024)
- Issue: 1, page 60-75
- ISSN: 0023-5954
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topCui, Yuxin, Li, Shu, and Shan, Yunxiao. "Finite-time observability of probabilistic Boolean multiplex control networks." Kybernetika (2024): 60-75. <http://eudml.org/doc/299496>.
@article{Cui2024,
abstract = {This paper investigates the finite-time observability of probabilistic Boolean multiplex control networks (PBMCNs). Firstly, the finite-time observability of the PBMCNs is converted into the set reachability issue according to the parallel interconnection technique (a minor modification of the weighted pair graph method in the literature). Secondly, the necessary and sufficient condition for the finite-time observability of PBMCNs is presented based on the set reachability. Finally, the main conclusions are substantiated by providing illustrative examples.},
author = {Cui, Yuxin, Li, Shu, Shan, Yunxiao},
journal = {Kybernetika},
keywords = {finite-time observability; semi-tensor product; probabilistic Boolean multiplex control networks; set reachability},
language = {eng},
number = {1},
pages = {60-75},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Finite-time observability of probabilistic Boolean multiplex control networks},
url = {http://eudml.org/doc/299496},
year = {2024},
}
TY - JOUR
AU - Cui, Yuxin
AU - Li, Shu
AU - Shan, Yunxiao
TI - Finite-time observability of probabilistic Boolean multiplex control networks
JO - Kybernetika
PY - 2024
PB - Institute of Information Theory and Automation AS CR
IS - 1
SP - 60
EP - 75
AB - This paper investigates the finite-time observability of probabilistic Boolean multiplex control networks (PBMCNs). Firstly, the finite-time observability of the PBMCNs is converted into the set reachability issue according to the parallel interconnection technique (a minor modification of the weighted pair graph method in the literature). Secondly, the necessary and sufficient condition for the finite-time observability of PBMCNs is presented based on the set reachability. Finally, the main conclusions are substantiated by providing illustrative examples.
LA - eng
KW - finite-time observability; semi-tensor product; probabilistic Boolean multiplex control networks; set reachability
UR - http://eudml.org/doc/299496
ER -
References
top- Azuma, S. I., Yoshida, T., Sugie, T., , IEEE T. Control Netw. 6 (2018), 464-473. MR3958930DOI
- Chen, S. Q., Wu, Y. H., Macauley, M., Sun, X. M., , IEEE T. Contr. Syst. Theory 6 (2018), 1379-1390. MR4052461DOI
- Cheng, D., , IEEE Trans. Automat. Control 56 (2011), 2-10. MR2777196DOI
- Cheng, D. Z., Li, C., He, F., , Syst. Control Lett. 115 (2018), 22-25. MR3786117DOI
- Cheng, D., Qi, H., Liu, T., Wang, Y., , Syst. Control Lett. 87 (2016), 76-82. MR3433244DOI
- Cheng, D. Z., Qi, H. S., Zhao, Y., An Introduction to Semi-Tensor Product of Matrices and Its Applications., World Scientific Publishing Co. Pte. Ltd., Singapore 2012. MR2963878
- Cheng, D. Z., Wu, Y. H., Zhao, G., Fu, S., , J. Syst. Sci. Complex. 34 (2021), 1666-1680. MR4331641DOI
- Cui, Y. X., Li, S., Liu, F. Q., Wu, Y. H., , J. Liaocheng University (Natural Science Edition) (2023), 1-11. MR3379151DOI
- Cui, Y. X., Li, S., Shan, Y. X., Liu, F. Q., , Appl. Sci. Basel 12 (2022), 883. DOI
- Fu, S., Pan, Y., Feng, J. E., Zhao, J., , Int. J. Control 95, (2022), 562-571. MR4372084DOI
- Guo, Y. Q., , IEEE T. Neur. Net. Learn. 29 (2018), 6402-6408. MR3891710DOI
- Heidel, J., Maloney, J., Farrow, C., Rogers, J.A., 10.1142/S0218127403006765, Int. J. Bifurcat. Chaos 13 (2003), 535-552. MR1981054DOI10.1142/S0218127403006765
- Kauffman, S. A., , J. Theor. Biol. 22 (1968), 437-467. MR2436652DOI
- Kauffman, S. A., At home in the universe., Math. Soc. Sci. 1 (1997), 94-95. MR1626501
- Kitano, H., 10.1126/science.1069492, Science 295 (2002), 1662-1664. DOI10.1126/science.1069492
- Laschov, D., Margaliot, M., Even, G., , Automatica 49 (2013), 2351-2362. MR3072626DOI
- Le, S. T., Wu, Y. H., Toyoda, M., , Inform. Science 514 (2020), 512-522. MR4046121DOI
- Li, Y., Feng, J. E., Wang, B., , Infrom. Sci. 612 (2022), 612-625. DOI
- Li, Y., Feng, J. E., Zhu, S., , Circ. Syst. Signal PR 40 (2021), 1-16. MR1396882DOI
- Fornasini, E., Valcher, M., , IEEE Contr. Syst. Lett. 4 (2019), 319-324. MR4211304DOI
- Li, F., Ho, D., , IEEE T. Circuits-II. 67 (2019), 1989-1993. DOI
- Li, F., Sun, J., , IET Control Theory A 5 (2011), 1609-1616. MR2883333DOI
- Li, F., Sun, J., Wu, Q., , IEEE Trans. Neural Netw. 22 (2011), 948-954. DOI
- Liu, Y., Zhong, J., Ho, D. W., Gui, W., , Sci. China Inform. Sci. 65 (2022), 1-12. MR4404189DOI
- Liu, Y., Wang, L., Yang, Y., Wu, Z. G., , Syst. Control Lett. 163 (2022), 105204. MR4405482DOI
- Li, Y., Feng, J. E., Wang, B., , J. Franklin I. 359 (2022), 331-351. MR4364957DOI
- Li, R., Zhang, Q., Zhang, J., Chu, T., , Syst. Control Lett. 156 (2021), 105001. MR4299865DOI
- Liu, Y., Cao, J., Wang, L., Wu, Z. G., , IET Control Theory A 63 (2020), 1-3. MR4013798DOI
- Liu, Z., Zhong, J., Liu, Y., Gui, W., , IEEE T. Neur. Net. Learn. 5 (2021), 2693-2700. MR4589423DOI
- Lu, J., Zhong, J., Huang, C., Cao, J., , IEEE T. Automat. Control 61 (2015), 1658-1663. MR3508713DOI
- Machado, A. M., Bazzan, A. L., Self-adaptation in a network of social drivers: Using random boolean networks., In: Proc. 2011 Workshop on Organic Computing, Paris 2011, pp. 33-40.
- Meng, M., Li, L., , IEEE T. Circuits II 69 (2022), 3565-3569. DOI
- Pan, Q., Zhong, J., Lin, L., Lin, B., Liu, X., , Asian J. Control 25 (2022), 325-334. MR4562337DOI
- Toyoda, M., Wu, Y. H., , IEEE T. Cybernetics 51 (2021), 3079-3092. DOI
- Wang, J., Liu, Y., Li, H., , IEEE Access 8 (2020), 111995-112002. DOI
- Wang, L., Liu, Y., Wu, Z. G., Lu, J., Yu, L., , IEEE T. Syst. Man CY-S. 51 (2019), 1599-1566. MR3901770DOI
- Wu, Y. H., Cheng, D. Z., Ghosh, B. K., Shen, T., , Asian J. Control 21 (2019), 2493-2512. MR4067608DOI
- Wu, G., Dai, L., Liu, Z., Chen, T., Pan, J., , IFAC - PapersOnLine 53 (2020), 1057-1064. DOI
- Wu, Y. H., Guo, Y. Q., Toyoda, M., , IEEE T. Neur. Net. Learn. 32 (2020), 2910-2924. MR4285216DOI
- Wu, Y. H., Sun, X. M., Zhao, X., Shen, T. L., , Automatica 100 (2019), 378-387. MR3885198DOI
- Wu, Y. H., Xu, J., Sun, X., Wang, W., , Sci. Rep. 7 (2017), 46495. DOI
- Yu, Y., Meng, M., Feng, J. E., , Automatica 111 (2020), 108621. MR4039368DOI
- Zhu, S., Feng, J. E., Zhao, J., , Discrete Cont. Dyn. Syst. 14 (2021), 1591-1605. MR4220582DOI
- Zhu, Q., Liu, Y., Lu, J., Cao, J., , IEEE T. Control Netw. 6 (2018), 1291-1301. MR4052453DOI
- Zhang, Q. L., Feng, J. E., Wang, B., , IET Control Theory A 14 (2020), 2914-2923. MR4418022DOI
- Zhang, K., Zhang, L., , IEEE T. Automat. Control 61 (2016), 2733-2738. MR3545104DOI
- Zhang, K., Zhang, L., Xie, L., , Nonlinear Anal-Hybri. 19 (2016), 186-197. MR3425354DOI
- Zhong, J., Lu, J., Huang, T., Ho, D. W., , IEEE T. Cybernetics 47 (2017), 3482-3493. DOI
- Zhou, R., Guo, Y. Q., Gui, W., , Automatica 106 (2019), 230-241. MR3952584DOI
- Zhu, Q., Liu, Y., Lu, J., Cao, J., , Sci. China Inform. Sci. 61 (2018), 1-12. MR3718227DOI
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