[1] Bu, X., Dong, H., Han, F., Hou, N., Li, G.:
Distributed filtering for time-varying systems over sensor networks with randomly switching topologies under the Round-Robin protocol. Neurocomputing 346 (2019), 58-64.
DOI 10.1016/j.neucom.2018.07.087 |
MR 4044317
[2] Chen, W., Ding, D., Ge, X., Han, Q.-L., Wei, G.:
H-infinity containment control of multi-agent systems under event-triggered communication scheduling: The finite-horizon case. IEEE Trans. Cybernetics (2018), 1-11.
DOI 10.1109/tcyb.2018.2885567
[3] Ding, D., Han, Q.-L., Wang, Z., Ge, X.:
A survey on model-based distributed control and filtering for industrial cyber-physical systems. IEEE Trans. Industr. Inform. 15 (2019), 2483-2499.
DOI 10.1109/tii.2019.2905295
[4] Ding, D., Wang, Z., Han, Q.-L.:
A set-membership approach to event-triggered filtering for general nonlinear systems over sensor networks. IEEE Trans. Automat. Control (2019), 1.
DOI 10.1109/tac.2019.2934389
[5] Ding, D., Wang, Z., Han, Q.-L., Wei, G.:
Neural-network-based output-feedback control under Round-Robin scheduling protocols. IEEE Trans. Cybernetics 49 (2019), 2372-2384.
DOI 10.1109/tcyb.2018.2827037
[7] Dong, H., Hou, N., Wang, Z., Liu, H.:
Finite-horizon fault estimation under imperfect measurements and stochastic communication protocol: Dealing with finite-time boundedness. Int. J. Robust Nonlinear Control 29 (2019), 117-134.
DOI 10.1002/rnc.4382 |
MR 3886112
[8] Dong, H., Wang, Z., Ding, S. X., Gao, H.:
Finite-horizon estimation of randomly occurring faults for a class of nonlinear time-varying systems. Automatica 50 (2014), 3182-3189.
DOI 10.1016/j.automatica.2014.10.026 |
MR 3284153
[9] Dong, H., Wang, Z., Ding, S. X., Gao, H.:
On $H_\infty$ estimation of randomly occurring faults for a class of nonlinear time-varying systems with fading channels. IEEE Trans. Automat. Control 61 (2015), 479-484.
DOI 10.1109/tac.2015.2437526 |
MR 3454754
[10] Gao, M., Yang, S., Sheng, L., Zhou, D.:
Fault diagnosis for time-varying systems with multiplicative noises over sensor networks subject to Round-Robin protocol. Neurocomputing 346 (2019), 65-72.
DOI 10.1016/j.neucom.2018.08.087
[11] Ge, X., Han, Q.-L., Wang, Z.:
A threshold-parameter-dependent approach to designing distributed event-triggered $H_\infty$ consensus filters over sensor networks. IEEE Trans. Cybernetics 49 (2019), 1148-1159.
DOI 10.1109/tcyb.2017.2789296
[12] Ge, X., Han, Q.-L., Wang, Z.:
A dynamic event-triggered transmission scheme for distributed set-membership estimation over wireless sensor networks. IEEE Trans. Cybernetics 49 (2019), 171-183.
DOI 10.1109/tcyb.2017.2769722
[13] Hou, N., Wang, Z., Ho, D. W. C., Dong, H.:
Robust Partial-Nodes-Based state estimation for complex networks under deception attacks. IEEE Trans. Cybernetics (2019), 1-10.
DOI 10.1109/TCYB.2019.2918760
[14] Hu, J., Wang, Z., Gao, H.:
Joint state and fault estimation for time-varying nonlinear systems with randomly occurring faults and sensor saturations. Automatica 97 (2018), 150-160.
DOI 10.1016/j.automatica.2018.07.027 |
MR 3857456
[15] Li, J., Dong, H., Wang, Z., Bu, X.:
Partial-Neurons-Based passivity-guaranteed state estimation for neural networks with randomly occurring time-delays. IEEE Trans. Neural Networks Learn. Systems (2019), 1-7.
DOI 10.1109/tnnls.2019.2944552
[16] Li, J., Dong, H., Wang, Z., Hou, N., Alsaadi, F. E.:
On passivity and robust passivity for discrete-time stochastic neural networks with randomly occurring mixed time delays. Neural Computing Appl. 31 (2019), 65-78.
DOI 10.1007/s00521-017-2980-1
[17] Li, Q., Shen, B., Wang, Z., Huan, T., Luo, J.:
Synchronization control for a class of discrete time-delay complex dynamical networks: A dynamic event-triggered approach. IEEE Trans. Cybernetics 49 (2019), 1979-1986.
DOI 10.1109/tcyb.2018.2818941 |
MR 3891660
[18] Li, Y., Karimi, H. R., Zhang, Q., Zhao, D., Li, Y.:
Fault detection for linear discrete time-varying systems subject to random sensor delay: a Riccati equation approach. IEEE Trans. Circuits and Systems I: Regular Papers 65 (2018), 1707-1716.
DOI 10.1109/tcsi.2017.2763625
[19] Li, Z., Shu, H., Kan, X.:
$H_\infty$ fault detection with randomly occurring nonlinearities and channel fadings. Int. J. Systems Sci. 45 (2014), 1416-1426.
DOI 10.1109/tcsi.2017.2763625 |
MR 3219744
[21] Liu, Q., Wang, Z., He, X., Zhou, D.:
Event-triggered resilient filtering with measurement quantization and random sensor failures: Monotonicity and convergence. Automatica 94 (2018), 458-464.
DOI 10.1016/j.automatica.2018.03.031 |
MR 3810997
[22] Liu, Y., Wang, Z., Zhou, D.:
UIO-based fault estimation for a class of time-varying systems with event-triggered transmissions. IFAC-PapersOnLine 51 (2018), 46-51.
DOI 10.1016/j.ifacol.2018.09.527
[24] Shen, B., Wang, Z., Wang, D., Luo, J.:
Finite-horizon filtering for a class of nonlinear time-delayed systems with an energy harvesting sensor. Automatica 100 (2019), 144-152.
DOI 10.1016/j.automatica.2018.11.010 |
MR 3881144
[25] Shen, Y., Wang, Z., Shen, B., Alsaadi, F. E., Alsaadi, F. E.:
Fusion estimation for multi-rate linear repetitive processes under weighted Try-Once-Discard protocol. Inform. Fusion 55 (2020), 281-291.
DOI 10.1016/j.inffus.2019.08.013
[26] Sheng, L., Niu, Y., Zou, L., Liu, Y., Alsaadi, F. E.:
Finite-horizon state estimation for time-varying complex networks with random coupling strengths under Round-Robin protocol. J. Franklin Inst. 355 (2018), 7417-7442.
DOI 10.1016/j.jfranklin.2018.07.026 |
MR 3857394
[27] Sheng, L., Wang, Z., Zou, L., Alsaadi, F. E.:
Event-based $H_\infty$ state estimation for time-varying stochastic dynamical networks with state- and disturbance-dependent noises. IEEE Trans. Neural Networks Learn. Systems 28 (2017), 2382-2394.
DOI 10.1109/tnnls.2016.2580601 |
MR 3709755
[29] Wan, X., Wang, Z., Wu, M., Liu, X.:
State estimation for discrete time-delayed genetic regulatory networks with stochastic noises under the Round-Robin protocols. IEEE Trans. NanoBioscience 17 (2018), 145-154.
DOI 10.1109/tnb.2018.2797124
[30] 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.
MR 2479308
[31] Zhang, X.-M., Han, Q.-L.:
A decentralized event-triggered dissipative control scheme for systems with multiple sensors to sample the system outputs. IEEE Trans. Cybernet. 46 (2015), 2745-2757.
DOI 10.1109/tcyb.2015.2487420
[32] Zhang, X.-M., Han, Q.-L., Ge, X., Ding, D., Ding, L., Yue, D., Peng, C.:
Networked control systems: a survey of trends and techniques. IEEE/CAA J. Automat. Sinica (2019), 1-17.
DOI 10.1109/jas.2019.1911651 |
MR 3748030
[33] Zhu, J.-W., Yang, G.-H., Wang, H., Wang, F.:
Fault estimation for a class of nonlinear systems based on intermediate estimator. IEEE Trans. Automat. Control 61 (2016), 2518-2524.
DOI 10.1109/tac.2015.2491898 |
MR 3545070
[34] Zou, L., Wang, Z., Gao, H.:
Set-membership filtering for time-varying systems with mixed time-delays under Round-Robin and Weighted Try-Once-Discard protocols. Automatica 74 (2016), 341-348.
DOI 10.1016/j.automatica.2016.07.025 |
MR 3569400
[35] Zou, L., Wang, Z., Gao, H., Liu, X.:
State estimation for discrete-time dynamical networks with time-varying delays and stochastic disturbances under the Round-Robin protocol. IEEE Trans. Neural Networks Learn. Systems 28 (2017), 1139-1151.
DOI 10.1109/tnnls.2016.2524621 |
MR 3914858
[36] Zou, L., Wang, Z., Han, Q.-L., Zhou, D. H.:
Ultimate boundedness control for networked systems with Try-Once-Discard protocol and uniform quantization effects. IEEE Trans. Automat. Control 62 (2017), 6582-6588.
DOI 10.1109/tac.2017.2713353 |
MR 3743543
[37] Zou, L., Wang, Z., Zhou, D.:
Finite-horizon $H_\infty$ fault estimation for time-varying systems with Random Access protocol. IFAC-PapersOnLine 51 (2018), 314-319.
DOI 10.1016/j.ifacol.2018.09.595 |
MR 3912120
[38] Zuo, Z., Han, Q.-L., Ning, B., Ge, X., Zhang, X.-M.:
An overview of recent advances in fixed-time cooperative control of multi-agent systems. IEEE Trans. Industr. Inform. 14(2018), 2322-2334.
DOI 10.1109/tii.2018.2817248 |
MR 3932129