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Keywords:
Takagi--Sugeno fuzzy system; exponentially ultimately boundness; non-fragile estimation; robust optimization
Takagi--Sugeno fuzzy system; exponentially ultimately boundness; non-fragile estimation; robust optimization
Summary:
This paper investigates the non-fragile state estimation problem for a class of discrete-time T-S fuzzy systems with time-delays and multiple missing measurements under event-triggered mechanism. First of all, the plant is subject to the time-varying delays and the stochastic disturbances. Next, a random white sequence, the element of which obeys a general probabilistic distribution defined on $[0,1]$, is utilized to formulate the occurrence of the missing measurements. Also, an event generator function is employed to regulate the transmission of data to save the precious energy. Then, a non-fragile state estimator is constructed to reflect the randomly occurring gain variations in the implementing process. By means of the Lyapunov-Krasovskii functional, the desired sufficient conditions are obtained such that the Takagi-Sugeno (T-S) fuzzy estimation error system is exponentially ultimately bounded in the mean square. And then the upper bound is minimized via the robust optimization technique and the estimator gain matrices can be calculated. Finally, a simulation example is utilized to demonstrate the effectiveness of the state estimation scheme proposed in this paper.
References:
[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. Cybernet. 59 (2020), 4, 1372-1382. DOI 10.1109/tcyb.2018.2885567
[3] Chen, W., Zhong, J., Zheng, W.: Delay-independent stabilization of a class of time-delay systems via periodically intermittent control. Automatica 71 (2016), 89-97. DOI 10.1016/j.automatica.2016.04.031 | MR 3521957
[4] 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
[5] Ding, D., Wang, Z., Han, Q.-L., Wei, G.: Neural-network-based output-feedback control under Round-Robin scheduling protocols. IEEE Trans. Cybernet. 49 (2019), 2372-2384. DOI 10.1109/tii.2019.2905295
[6] Dong, H., Bu, X., Hou, N., Liu, Y., Alsaadi, F. E., Hayat, T.: Event-triggered distributed state estimation for a class of time-varying systems over sensor networks with redundant channels. Inform. Fusion 36 (2017), 243-250. DOI 10.1016/j.inffus.2016.12.005
[7] Ding, D., Wang, Z., Wei, G., Alsaadi, F. E.: Event-based security control for discrete-time stochastic systems. IET Control Theory Appl. 10 (2016), 1808-1815. DOI 10.1049/iet-cta.2016.0135 | MR 3587315
[8] 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. Cybernet. 49 (2019),1148-1159. DOI 10.1109/tcyb.2017.2789296
[9] Ge, X., Han, Q.-L., Wang, Z.: A dynamic event-triggered transmission scheme for distributed set-membership estimation over wireless sensor networks. IEEE Trans. Cybernet. 49 (2019), 171-183. DOI 10.1109/tcyb.2017.2769722
[10] Ge, X., Han, Q.-L.: Consensus of multiagent systems subject to partially accessible and overlapping Markovian network topologies. IEEE Trans. Cybernet. 47 (2017), 1807-1819. DOI 10.1109/tcyb.2016.2570860
[11] 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
[12] Guan, X., Chen, C.: Delay-dependent guaranteed cost control for T-S fuzzy systems with time delays. IEEE Trans. Fuzzy System 12 (2004), 236-249. DOI 10.1109/TFUZZ.2004.825085 | MR 2096656
[13] Han, F., Song, Y., Zhang, S., Li, W.: Local condition-based finite-horizon distributed $H_{\infty}$-consensus filtering for random parameter system with event-triggering protocols. Neruocomputing 219 (2017), 221-231. DOI 10.1016/j.neucom.2016.09.022
[14] Han, F., Ding, D., Yang., F., Gao, W.: Distributed resilient estimation for nonlinear delay systems with stochastic perturbations. Int. J. Robust Nonlinear Control 30 (2020) 843-863. DOI 10.1002/rnc.4783
[15] Hu, J., Chen, D., Du, J.: State estimation for a class of discrete nonlinear systems with randomly occurring uncertainties and distributed sensor delays. Int. J. General Systems 43 (2014), 387-401. DOI 10.1080/03081079.2014.892251 | MR 3177030
[16] Hu, J., Liang, J., Chen, D.: A recursive approach to non-fragile filtering for networked systems with stochastic uncertainties and incomplete measurements. J. Franklin Inst. 352 (2015), 1946-1962. DOI 10.1016/j.jfranklin.2015.02.002 | MR 3334122
[17] Liu, Y., Guo, B., Park, J.: Non-fragile $H_{\infty}$ filtering for delayed Takagi-Sugeno fuzzy systems with randomly occurring gain variations. Fuzzy Sets Systems 316 (2017), 99-116. DOI 10.1016/j.fss.2016.11.001 | MR 3623196
[18] Ko, J. W., Park, P. G.: Further enhancement of stability and stabilisability margin for Takagi-Sugeno fuzzy systems. IET Control Theory 6 (2012), 313-318. DOI 10.1049/iet-cta.2011.0009 | MR 2932086
[19] Liu, Y., Wang, Z., Liang, J., Liu, X.: Synchronization and state estimation for discrete-time complex networks with distributed delays. IEEE Trans. Cybernet. 38 (2008), 1314-1325. DOI 10.1109/tsmcb.2008.925745
[20] Li, Q., Shen, B., Wang, Z.: An event-triggered approach to distributed $H_{\infty}$ state estimation for state-saturated systems with randomly occurring mixed delays. J. Franklin Inst. 355 (2018), 3104-3121. DOI 10.1016/j.jfranklin.2018.02.007 | MR 3778262
[21] Li, Q., Shen, B., Liu, Y., Alsaadi, F. E.: Event-triggered $H_{\infty}$ state estimation for discrete-time stochastic genetic regulatory networks with Markovian jumping parameters and time-varying delays. Neurocomputing {\mi174} (2016), 912-920. DOI 10.1016/j.neucom.2015.10.017
[22] 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 Learning Syst. (2019), 1-7.
[23] 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
[24] Lian, Z., He, Y., Zhang, C.: Stability analysis for T-S fuzzy systems with time-varying delay via free-matrix-based integral inequality. Int. Control Automat. Syst. 14 (2016), 21-28. DOI 10.1007/s12555-015-2001-z | MR 3774604
[25] Liu, Y., Wang, Z., He, X., Zhou, D.: Filtering and fault detection for nonlinear systems with polynomial approximation. Automatica 54 (2015), 348-359. DOI 10.1016/j.automatica.2015.02.022 | MR 3324541
[26] Liu, Y., Wang, Z., Zhou, D.: Quantised polynomial filtering for nonlinear systems with missing measurement. Int. J. Control 91 (2018), 2250-2260. DOI 10.1080/00207179.2017.1337933 | MR 3857116
[27] Liu, J., Liu, Q., Cao, J.: Adaptive event-triggered $H_{\infty}$ filtering for T-S fuzzy system with time delay. Neurocomputing 189 (2016), 86-94. DOI 10.1016/j.neucom.2015.12.049
[28] Ma, L., Wang, Z., Liu, Y., Alsaadi, F. E.: A note on guaranteed cost control for nonlinear stochastic systems with input saturation and mixed time-delays. Int. J. Robust Nonlinear Control 27 (2017), 4443-4456. DOI 10.1002/rnc.3809 | MR 3733677
[29] Shi, P., Zhang, Y., Agarwal, R. K.: Stochastic finite-time state estimation for discrete time-delay neural networks with Markovian jumps. Neurocomputing 151 (2015), 168-174. DOI 10.1016/j.neucom.2014.09.059
[30] Sheng, L., Niu, Y., Gao, M.: Distributed resilient filtering for time-varying systems over sensor networks subject to Round-Robin/stochastic protocol. ISA Trans. 87 (2019), 55-67. DOI 10.1016/j.isatra.2018.11.012
[31] Sheng, L., Wang, Z., Zou, L., Alsaadi, F.: Event-based $H_{\infty}$ state estimation for time-varying stochastic dynamical networks with state- and disturbance-dependent noises. IEEE Trans. Neural Networks Learning Syst. 28 (2017), 2382-2394. DOI 10.1109/tnnls.2016.2580601 | MR 3709755
[32] Shen, Y., Wang, Z., Shen, B., Alsaadi, Fa. 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
[33] Tong, M., Lin, W., Huo, X., Jin, Z.: A model-free fuzzy adaptive trajectory tracking control algorithm based on dynamic surface control. Int. J. Advanced Robotic Syst. 17 (2020), 1, 1729881419894417. DOI 10.1177/1729881419894417
[34] Tian, E., Wang, Z., Zou, L., Yue, D.: Probability-constrained filtering for a class of nonlinear systems with improved static event-triggered communication. Int. J. Robust and Nonlinear Control 29 (2019), 1484-1498. DOI 10.1002/rnc.4447 | MR 3915146
[35] Takagi, T., Sugeno, M.: Fuzzy identification of systems and its application to modelling and control. IEEE Trans. Systems Man Cybernet. SMC-15 (1985), 116-132
[36] Yu, Y., Dong, H., Wang, Z.: Design of non-fragile state estimators for discrete time-delayed neural networks with parameter uncertainties. Neurocomputing 182 (2016), 18-24. DOI 10.1016/j.neucom.2015.11.079
[37] Yan, H., Qian, F., Yang, F.: $H_{\infty}$ filtering for nonlinear networked systems with randomly occurring distributed delays, missing measurements and sensor saturation. Inform. Sci. 370 (2016), 772-782. DOI 10.1016/j.ins.2015.09.027
[38] Wang, L., Wang, Z., Huang, T., Wei, G.: An event-triggered approach to state estimation for a class of complex networks with mixed time delays and nonlinearities. IEEE Trans. Cybernet. 46 (2016), 2497-2508. DOI 10.1109/tcyb.2015.2478860
[39] Wang, F., Wang, Z., Liang, J.: Resilient state estimation for 2-D time-varying systems with redundant channels: A variance-constrained approach. IEEE Trans. Cybernet. 49 (2019), 2479-2489. DOI 10.1109/tcyb.2018.2821188
[40] Wang, B., Cheng, J., Al-Barakati, A.: A mismatched membership function approach to sampled-data stabilization for T-S fuzzy systems with time-varying delayed signals. Signal Process. 140 (2017), 161-170. DOI 10.1016/j.sigpro.2017.05.018
[41] Wu, L., Su, X., Shi, P.: Robust filtering of discrete-time T-S fuzzy time-delay systems. In: Fuzzy Control Systems with Time-Delay and Stochastic Perturbation, Springer-Cham 2015, 79-113. DOI 10.1007/978-3-319-11316-6\_4 | MR 3525793
[42] Zhang, L., Ning, Z., Wang, Z.: Distributed filtering for fuzzy time-delay systems with packet dropouts and redundant channels. IEEE Trans. Systems Man Cybernet.: Systems 46 (2016), 559-572. DOI 10.1109/tsmc.2015.2435700
[43] Zhang, D., Shi, P., Wang, Q.: Distributed non-fragile filtering for T-S fuzzy systems with event-based communications. Fuzzy Sets Syst. 306 (2017), 137-152. DOI 10.1016/j.fss.2016.02.009 | MR 3567161
[44] Zou, L., Wang, Z., Gao, H., Liu, X.: Event-triggered state estimation for complex networks with mixed time delays via sampled data information: the continuous-time case. IEEE Trans. Cybernet. 45 (2015), 2804-2815. DOI 10.1109/tcyb.2014.2386781
[45] Zhang, S., Wang, Z., Ding, D., Wei, G., Alsaadi, F. E., Hayat, T.: A gain-scheduling approach to nonfragile $H_{\infty}$ fuzzy control subject to fading channels. IEEE Trans. Fuzzy Syst. 26 (2018), 142-154. DOI 10.1109/tfuzz.2016.2641023
[46] Zhe, D., Zheng, Y.: Finite-horizon robust Kalman filtering for uncertain discrete time-varying systems with uncertain-covariance white noises. IEEE Signal Process. Lett. 13 (2006), 493-496. DOI 10.1109/lsp.2006.873148
[47] Zhang, X., Han, Q., 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
[48] Zuo, Z., Han, Q., Ning, B., Ge, X., Zhang, X.: 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
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