×

Adaptive event-triggered asynchronous fault-tolerant control for stochastic systems with multiple-types of failures. (English) Zbl 07842350

Summary: This article studies a kind of asynchronous fault-tolerant control problem for stochastic systems (Markov jump systems, MJSs) with multiple-types of actuator failures. Both the loss of effectiveness and stuck fault of actuator are taken into consideration in a unified actuator failures model. The asynchronization phenomenon between the controller and the original system is described by a hidden Markov model. By coupling the unknown stuck fault of actuator and the external disturbances together, the stuck fault and disturbance can be estimated simultaneously. After this, a fault-tolerant controller based on the estimated values is designed further to automatically compensate for the faults while preserving the uniformly ultimate boundedness of the solutions. Moreover, a mode-dependent adaptive event-triggered mechanism is introduced to limit the number of packets sent on the network. Finally, a numerical example is employed to illustrate the effectiveness of the proposed design scheme.
{© 2022 John Wiley & Sons Ltd.}

MSC:

93E35 Stochastic learning and adaptive control
60J28 Applications of continuous-time Markov processes on discrete state spaces
Full Text: DOI

References:

[1] WuZ, DongS, ShiP, SuH, HuangT, LuR. Fuzzy‐model‐based nonfragile guaranteed cost control of nonlinear Markov jump systems. IEEE Trans Syst Man Cybern Syst. 2017;47(8):2388‐2397.
[2] ShenH, MenY, WuZ, CaoJ, LuG. Network‐based quantized control for fuzzy singularly perturbed semi‐Markov jump systems and its application. IEEE Trans Circuits Syst I Regul Pap. 2019;66(3):1130‐1140.
[3] LianJ, LiS, LiuJ. T‐S fuzzy control of positive Markov jump nonlinear systems. IEEE Trans Fuzzy Syst. 2018;26:2870‐2885.
[4] ZhangM, ShiP, MaL, CaiJ, SuH. Network‐based fuzzy control for nonlinear Markov jump systems subject to quantization and dropout compensation. Fuzzy Sets Syst. 2018;371:96‐109. · Zbl 1423.93226
[5] LuanT, ZhaoS, LiuF. H∞ control for discrete‐time Markov jump systems with uncertain transition probabilities. IEEE Trans Automat Contr. 2013;58(6):1566‐1572. · Zbl 1369.93178
[6] ShenH, MenY, WuZ, ParkJH. Nonfragile
[( {H}_{\infty } \]\) control for fuzzy Markovian jump systems under fast sampling singular perturbation. IEEE Trans Syst Man Cybern Syst. 2018;48(12):2058‐2069.
[7] WenJ, NguangS, ShiP, NasiriA. Robust
[( {H}_{\infty } \]\) control of discrete‐time nonhomogenous Markovian jump systems via multistep Lyapunov function approach. IEEE Trans Syst Man Cybern Syst. 2017;47(7):1439‐1450.
[8] LiangX, ZhangX. H∞ control for discrete‐time Markov jump linear systems via static output feedback. IEEE Access. 2019;7:145363‐145370.
[9] ZhuJ, YuX, ZhangT, CaoZ, YangY, YiY. The mean‐square stability probability of
[( {H}_{\infty } \]\) control of continuous Markovian jump systems. IEEE Trans Automat Contr. 2016;61(7):1918‐1924. · Zbl 1359.93527
[10] WuL, ShiP, GaoH. State estimation and sliding‐mode control of Markovian jump singular systems. IEEE Trans Automat Contr. 2010;55(5):1213‐1121. · Zbl 1368.93696
[11] ZhangQ, ZhangJ, WangY. Sliding‐mode control for singular Markovian jump systems with Brownian motion based on stochastic sliding mode surface. IEEE Trans Syst Man Cybern Syst. 2019;49(3):494‐505.
[12] QiW, ZongG, KarimiHR. Sliding mode control for nonlinear stochastic singular semi‐Markov jump systems. IEEE Trans Automat Contr. 2020;65(1):361‐368. · Zbl 1483.93612
[13] ZhangD, ZhangQ. Reduced‐order observer‐based sliding mode control for singular Markovian jump system with time‐varying transition rate. IEEE Trans Circuits Syst I Regul Pap. 2019;66(2):796‐809. · Zbl 1468.60095
[14] FengZ, ShiP. Sliding mode control of singular stochastic Markov jump systems. IEEE Trans Automat Contr. 2017;62(8):4266‐4273. · Zbl 1373.93305
[15] SongH, ChenS, YamY. Sliding mode control for discrete‐time systems with Markovian packet dropouts. IEEE Trans Cybern. 2017;47(11):3669‐3679.
[16] CaoZ, NiuY, LamHK, ZhaoJ. Sliding mode control of Markovian jump fuzzy systems: a dynamic event‐triggered method. IEEE Trans Fuzzy Syst. 2021;29(10):2902‐2915.
[17] OliveiraAM, CostaOLV. An iterative approach for the discrete‐time dynamic control of Markov jump linear systems with partial information. Int J Robust Nonlinear Control. 2020;30(2):49‐511. · Zbl 1440.93242
[18] WuZ, ShiP, ShuZ, SuH, LuR. Passivity‐based asynchronous control for Markov jump systems. IEEE Trans Automat Contr. 2017;62(4):2020‐2025. · Zbl 1366.93611
[19] SongJ, NiuY, ZhouY. Asynchronous sliding mode control of Markovian jump systems with time‐varying delays and partly accessible mode detection probabilities. Automatica. 2018;93:33‐41. · Zbl 1400.93052
[20] LiF, DuC, YangC, GuiW. Passivity‐based asynchronous sliding mode control for delayed singular Markovian jump systems. IEEE Trans Automat Contr. 2018;63(8):2715‐2721. · Zbl 1423.93365
[21] OliveiraA, CostaO. Mixed
[( {H}_{\infty } \]\) and
[( {H}_2 \]\) control of hidden Markov jump systems. Int J Robust Nonlinear Control. 2018;28(4):1261‐1280. · Zbl 1390.93722
[22] LiuY, FangF, ParkJ, KimH, YiX. Asynchronous output feedback dissipative control of Markovian jump systems with input time delay and quantized measurements. Nolinear Anal Hybrid Syst. 2019;31:109‐122. · Zbl 1408.93140
[23] ShenY, WuZ, ShiP, ShuZ, KarimiH. H∞ control of Markov jump time‐delay systems under asynchronous controller and quantizer. Automatica. 2019;99:352‐360. · Zbl 1406.93374
[24] SongJ, NiuY, XuJ. An Event‐triggered approach to sliding mode control of Markovian jump Lur’e systems under hidden mode detections. IEEE Trans Syst Man Cybern Syst. 2020;50(4):1514‐1525.
[25] XuY, WangY, ZhuangG, LuJ. Dynamic event‐based asynchronous
[( {H}_{\infty } \]\) control for T‐S fuzzy singular Markov jump systems with redundant channels. IET Control Theory Appl. 2019;13(14):2239‐2251. · Zbl 07907020
[26] YanH, ZhangH, YangF, ZhanX, PengC. Event‐triggered asynchronous guaranteed cost control for Markov jump systems discrete‐time neural networks with distributed delay and channel fading. IEEE Trans Neural Netw Learn Syst. 2018;29(8):3588‐3598.
[27] ChengJ, ParkJH, ZhangL, ZhuY. An asynchronous operation approach to event‐triggered control for fuzzy Markovian jump systems with general switching policies. IEEE Trans Fuzzy Syst. 2018;26(1):6‐18.
[28] ShenH, ChenM, WuZ, CaoJ, ParkJH. Reliable event‐triggered asynchronous extended passive control for semi‐Markov jump fuzzy systems and its application. IEEE Trans Fuzzy Syst. 2020;28(8):1708‐1722. doi:10.1109/TFUZZ.2019.2921264
[29] GuZ, TianE, LiuJ. Adaptive event‐triggered control of a class of nonlinear networked systems. J Franklin Inst. 2017;354:3854‐3871. · Zbl 1367.93362
[30] LiJ, PanY, SuH, WenC. Stochastic reliable control of a class of networked control systems with actuator faults and input saturation. Int J Control Autom Syst. 2014;12(3):564‐571.
[31] LiJ, GuK, LiuX, XuX. Asynchronous adaptive fault‐tolerant control for Markov jump systems with actuator failures and unknown nonlinear disturbances. Complexity. 2020;1‐10. · Zbl 1435.93161
[32] TaoJ, LuR, ShiP, SuH, WuZ. Dissipativity‐based reliable control for fuzzy Markov jump systems with actuator faults. IEEE Trans Cybern. 2017;47(9):2377‐2388.
[33] DongS, WuZ, ShiP, SuH, LuR. Reliable control of fuzzy systems with quantization and switched actuator failures. IEEE Trans Syst Man Cybern Syst. 2017;47(8):2198‐2208.
[34] ZhaiD, LiuX, XiC, WangH. Adaptive reliable
[( {H}_{\infty } \]\) control for a class of T‐S fuzzy systems with stochastic actuator failures. IEEE Access. 2017;5:22750‐22759.
[35] WeiY, QiuJ, ShiP, WuL. A piecewise‐Markovian Lyapunov approach to reliable output feedback control for fuzzy‐affine systems with time‐dlays and actuator faults. IEEE Trans Cybern. 2018;48(9):2723‐2735.
[36] LiJ, LiuX, RuX, XuX. Disturbance rejection adaptive fault‐tolerant constrained consensus for multi‐agent systems with failures. IEEE Trans Circuits Syst II Express Briefs. 2020;67(12):3302‐3306.
[37] LiJ, LiL. Reliable control for bilateral teleoperation systems with actuator faults using fuzzy disturbance observer. IET Control Theory Appl. 2017;11(3):446‐455.
[38] JinX, CheW, WuZ, et al. Analog control circuit designs for a class of continuous‐time adaptive fault‐tolerant control systems. IEEE Trans Cybern. 2020. doi:10.1109/TCYB.2020.3024913
[39] LiJ, XuY, GuK, LiL, XuX. Mixed passive/
[( {H}_{\infty } \]\) hybrid control for delayed Markovian jump system with actuator constraints and fault alarm. Int J Robust Nonlinear Control. 2018;28:6016‐6037. · Zbl 1405.93126
[40] JinX, LüS, YuJ. Adaptive NN‐based consensus for a class of nonlinear multiagent systems with actuator faults and faulty networks. IEEE Trans Neural Netw Learn Syst. 2021. doi:10.1109/TNNLS.2021.3053112
[41] WangH, ShiP, LimC, XueQ. Event‐triggered control for networked Markovian jump systems. Int J Robust Nonlinear Control. 2015;25(17):3422‐3438. · Zbl 1338.93348
[42] SongJ, NiuY, XuJ. An event‐triggered approach to sliding mode control of Markovian jump Lur’e systems under hidden mode detections. IEEE Trans Syst Man Cybern Syst. 2020;50(4):1514‐1525.
[43] YeD, ChenM, YangH. Distributed adaptive event‐triggered fault‐tolerant consensus of multiagent systems with general linear dynamics. IEEE Trans Cybern. 2019;49(3):757‐767.
[44] LiJ, RenW. Finite‐horizon
[( {H}_{\infty } \]\) fault‐tolerant constrained consensus for multiagent systems with communication delays. IEEE Trans Cybern. 2021;51(1):416‐426.
[45] HornR, JohnsonC. Matrix Analysis. Cambridge University Press; 1987.
[46] XieL. Output feedback
[( {H}_{\infty } \]\) control of system with parameter uncertainty. Int J Control. 1996;63:741‐750. · Zbl 0841.93014
[47] ChenL, LiuM, HuangX, HuS, QiuJ. Adaptive fuzzy sliding mode control for network‐based nonlinear systems with actuator failures. IEEE Trans Fuzzy Syst. 2018;26(3):1311‐1323.
[48] KhalilH. Nonlinear Systems. 3rd ed.Prentice Hall; 2002. · Zbl 1003.34002
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.