Fault estimation for time-varying systems with Round-Robin protocol
Haijing Fu; Hongli Dong; Jinbo Song; Nan Hou; Gongfa Li
Kybernetika (2020)
- Volume: 56, Issue: 1, page 107-126
- ISSN: 0023-5954
Access Full Article
topAbstract
topHow to cite
topFu, Haijing, et al. "Fault estimation for time-varying systems with Round-Robin protocol." Kybernetika 56.1 (2020): 107-126. <http://eudml.org/doc/297177>.
@article{Fu2020,
abstract = {This paper is concerned with the design problem of finite-horizon $H_\infty $ fault estimator for a class of nonlinear time-varying systems with Round-Robin protocol scheduling. The faults are assumed to occur in a random way governed by a Bernoulli distributed white sequence. The communication between the sensor nodes and fault estimators is implemented via a shared network. In order to prevent the data from collisions, a Round-Robin protocol is utilized to orchestrate the transmission of sensor nodes. By means of the stochastic analysis technique and the completing squares method, a necessary and sufficient condition is established for the existence of fault estimator ensuring that the estimation error dynamics satisfies the prescribed $H_\infty $ constraint. The time-varying parameters of fault estimator are obtained by recursively solving a set of coupled backward Riccati difference equations. A simulation example is given to demonstrate the effectiveness of the proposed design scheme of the fault estimator.},
author = {Fu, Haijing, Dong, Hongli, Song, Jinbo, Hou, Nan, Li, Gongfa},
journal = {Kybernetika},
keywords = {fault estimation; Round--Robin protocol; randomly occurring faults; Riccati difference equations; nonlinear time-varying system},
language = {eng},
number = {1},
pages = {107-126},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Fault estimation for time-varying systems with Round-Robin protocol},
url = {http://eudml.org/doc/297177},
volume = {56},
year = {2020},
}
TY - JOUR
AU - Fu, Haijing
AU - Dong, Hongli
AU - Song, Jinbo
AU - Hou, Nan
AU - Li, Gongfa
TI - Fault estimation for time-varying systems with Round-Robin protocol
JO - Kybernetika
PY - 2020
PB - Institute of Information Theory and Automation AS CR
VL - 56
IS - 1
SP - 107
EP - 126
AB - This paper is concerned with the design problem of finite-horizon $H_\infty $ fault estimator for a class of nonlinear time-varying systems with Round-Robin protocol scheduling. The faults are assumed to occur in a random way governed by a Bernoulli distributed white sequence. The communication between the sensor nodes and fault estimators is implemented via a shared network. In order to prevent the data from collisions, a Round-Robin protocol is utilized to orchestrate the transmission of sensor nodes. By means of the stochastic analysis technique and the completing squares method, a necessary and sufficient condition is established for the existence of fault estimator ensuring that the estimation error dynamics satisfies the prescribed $H_\infty $ constraint. The time-varying parameters of fault estimator are obtained by recursively solving a set of coupled backward Riccati difference equations. A simulation example is given to demonstrate the effectiveness of the proposed design scheme of the fault estimator.
LA - eng
KW - fault estimation; Round--Robin protocol; randomly occurring faults; Riccati difference equations; nonlinear time-varying system
UR - http://eudml.org/doc/297177
ER -
References
top- Bu, X., Dong, H., Han, F., Hou, N., Li, G., 10.1016/j.neucom.2018.07.087, Neurocomputing 346 (2019), 58-64. MR4044317DOI10.1016/j.neucom.2018.07.087
- Chen, W., Ding, D., Ge, X., Han, Q.-L., Wei, G., 10.1109/tcyb.2018.2885567, IEEE Trans. Cybernetics (2018), 1-11. DOI10.1109/tcyb.2018.2885567
- Ding, D., Han, Q.-L., Wang, Z., Ge, X., 10.1109/tii.2019.2905295, IEEE Trans. Industr. Inform. 15 (2019), 2483-2499. DOI10.1109/tii.2019.2905295
- Ding, D., Wang, Z., Han, Q.-L., 10.1109/tac.2019.2934389, IEEE Trans. Automat. Control (2019), 1. DOI10.1109/tac.2019.2934389
- Ding, D., Wang, Z., Han, Q.-L., Wei, G., 10.1109/tcyb.2018.2827037, IEEE Trans. Cybernetics 49 (2019), 2372-2384. DOI10.1109/tcyb.2018.2827037
- Dong, H., Hou, N., Wang, Z., 10.1016/j.automatica.2019.108734, Automatica 112 (2020), 108734. MR4043012DOI10.1016/j.automatica.2019.108734
- Dong, H., Hou, N., Wang, Z., Liu, H., 10.1002/rnc.4382, Int. J. Robust Nonlinear Control 29 (2019), 117-134. MR3886112DOI10.1002/rnc.4382
- Dong, H., Wang, Z., Ding, S. X., Gao, H., 10.1016/j.automatica.2014.10.026, Automatica 50 (2014), 3182-3189. MR3284153DOI10.1016/j.automatica.2014.10.026
- Dong, H., Wang, Z., Ding, S. X., Gao, H., 10.1109/tac.2015.2437526, IEEE Trans. Automat. Control 61 (2015), 479-484. MR3454754DOI10.1109/tac.2015.2437526
- Gao, M., Yang, S., Sheng, L., Zhou, D., 10.1016/j.neucom.2018.08.087, Neurocomputing 346 (2019), 65-72. DOI10.1016/j.neucom.2018.08.087
- Ge, X., Han, Q.-L., Wang, Z., 10.1109/tcyb.2017.2789296, IEEE Trans. Cybernetics 49 (2019), 1148-1159. DOI10.1109/tcyb.2017.2789296
- Ge, X., Han, Q.-L., Wang, Z., 10.1109/tcyb.2017.2769722, IEEE Trans. Cybernetics 49 (2019), 171-183. DOI10.1109/tcyb.2017.2769722
- Hou, N., Wang, Z., Ho, D. W. C., Dong, H., 10.1109/TCYB.2019.2918760, IEEE Trans. Cybernetics (2019), 1-10. DOI10.1109/TCYB.2019.2918760
- Hu, J., Wang, Z., Gao, H., 10.1016/j.automatica.2018.07.027, Automatica 97 (2018), 150-160. MR3857456DOI10.1016/j.automatica.2018.07.027
- Li, J., Dong, H., Wang, Z., Bu, X., 10.1109/tnnls.2019.2944552, IEEE Trans. Neural Networks Learn. Systems (2019), 1-7. DOI10.1109/tnnls.2019.2944552
- Li, J., Dong, H., Wang, Z., Hou, N., Alsaadi, F. E., 10.1007/s00521-017-2980-1, Neural Computing Appl. 31 (2019), 65-78. DOI10.1007/s00521-017-2980-1
- Li, Q., Shen, B., Wang, Z., Huan, T., Luo, J., 10.1109/tcyb.2018.2818941, IEEE Trans. Cybernetics 49 (2019), 1979-1986. MR3891660DOI10.1109/tcyb.2018.2818941
- Li, Y., Karimi, H. R., Zhang, Q., Zhao, D., Li, Y., 10.1109/tcsi.2017.2763625, IEEE Trans. Circuits and Systems I: Regular Papers 65 (2018), 1707-1716. DOI10.1109/tcsi.2017.2763625
- Li, Z., Shu, H., Kan, X., 10.1109/tcsi.2017.2763625, Int. J. Systems Sci. 45 (2014), 1416-1426. MR3219744DOI10.1109/tcsi.2017.2763625
- Liu, Q., Wang, Z., He, X., Zhou, D., 10.1007/978-3-030-00157-5_6, IEEE Trans. Automat. Control 64 (2018), 99-115. MR3936432DOI10.1007/978-3-030-00157-5_6
- Liu, Q., Wang, Z., He, X., Zhou, D., 10.1016/j.automatica.2018.03.031, Automatica 94 (2018), 458-464. MR3810997DOI10.1016/j.automatica.2018.03.031
- Liu, Y., Wang, Z., Zhou, D., 10.1016/j.ifacol.2018.09.527, IFAC-PapersOnLine 51 (2018), 46-51. DOI10.1016/j.ifacol.2018.09.527
- Penrose, R., Todd, J. A., 10.1017/s0305004100030929, Math. Proc. Cambridge Philosoph. Soc. 52 (1956), 17-19. MR0074092DOI10.1017/s0305004100030929
- Shen, B., Wang, Z., Wang, D., Luo, J., 10.1016/j.automatica.2018.11.010, Automatica 100 (2019), 144-152. MR3881144DOI10.1016/j.automatica.2018.11.010
- Shen, Y., Wang, Z., Shen, B., Alsaadi, F. E., Alsaadi, F. E., 10.1016/j.inffus.2019.08.013, Inform. Fusion 55 (2020), 281-291. DOI10.1016/j.inffus.2019.08.013
- Sheng, L., Niu, Y., Zou, L., Liu, Y., Alsaadi, F. E., 10.1016/j.jfranklin.2018.07.026, J. Franklin Inst. 355 (2018), 7417-7442. MR3857394DOI10.1016/j.jfranklin.2018.07.026
- Sheng, L., Wang, Z., Zou, L., Alsaadi, F. E., 10.1109/tnnls.2016.2580601, IEEE Trans. Neural Networks Learn. Systems 28 (2017), 2382-2394. MR3709755DOI10.1109/tnnls.2016.2580601
- Vesely, V., Ernek, M., 10.14736/kyb-2018-3-0593, Kybernetika 54 (2018), 593-609. MR3844834DOI10.14736/kyb-2018-3-0593
- Wan, X., Wang, Z., Wu, M., Liu, X., 10.1109/tnb.2018.2797124, IEEE Trans. NanoBioscience 17 (2018), 145-154. DOI10.1109/tnb.2018.2797124
- Wu, J., Weng, Z., Tian, Z., Shi, S., Fault tolerant control for uncertain time-delay systems based on sliding mode control., Kybernetika 44 (2008), 617-632. MR2479308
- Zhang, X.-M., Han, Q.-L., 10.1109/tcyb.2015.2487420, IEEE Trans. Cybernet. 46 (2015), 2745-2757. DOI10.1109/tcyb.2015.2487420
- Zhang, X.-M., Han, Q.-L., Ge, X., Ding, D., Ding, L., Yue, D., Peng, C., 10.1109/jas.2019.1911651, IEEE/CAA J. Automat. Sinica (2019), 1-17. MR3748030DOI10.1109/jas.2019.1911651
- Zhu, J.-W., Yang, G.-H., Wang, H., Wang, F., 10.1109/tac.2015.2491898, IEEE Trans. Automat. Control 61 (2016), 2518-2524. MR3545070DOI10.1109/tac.2015.2491898
- Zou, L., Wang, Z., Gao, H., 10.1016/j.automatica.2016.07.025, Automatica 74 (2016), 341-348. MR3569400DOI10.1016/j.automatica.2016.07.025
- Zou, L., Wang, Z., Gao, H., Liu, X., 10.1109/tnnls.2016.2524621, IEEE Trans. Neural Networks Learn. Systems 28 (2017), 1139-1151. MR3914858DOI10.1109/tnnls.2016.2524621
- Zou, L., Wang, Z., Han, Q.-L., Zhou, D. H., 10.1109/tac.2017.2713353, IEEE Trans. Automat. Control 62 (2017), 6582-6588. MR3743543DOI10.1109/tac.2017.2713353
- Zou, L., Wang, Z., Zhou, D., 10.1016/j.ifacol.2018.09.595, IFAC-PapersOnLine 51 (2018), 314-319. MR3912120DOI10.1016/j.ifacol.2018.09.595
- Zuo, Z., Han, Q.-L., Ning, B., Ge, X., Zhang, X.-M., 10.1109/tii.2018.2817248, IEEE Trans. Industr. Inform. 14(2018), 2322-2334. MR3932129DOI10.1109/tii.2018.2817248
NotesEmbed ?
topTo embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.