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Finite frequency fault detection for networked systems with access constraint. (English) Zbl 1373.93348

Summary: This paper addresses a fault detection strategy in finite frequency domain for networked system with communication constraints and packet loss. The considered communication constraint is that only one data packet can gain into the networks at each time-slot, and the fault detection filters complete the task with only partially available measurements. With consideration of the data packet loss and the stochastic scheduling protocol, a nonhomogeneous Markov jump system is firstly derived to describe the networked systems. For this class of systems, the generalized Kalman-Yakubovic-Popov lemma-based finite frequency fault detection filter design methods are invalid. To tackle this problem, a new mode-dependent lemma is developed to capture the system performance in finite frequency domain. Further, a set of fault detection filters are designed corresponding to the accessed nodes accordingly. Finally, an example is given to show the effectiveness of the proposed fault detection approach.

MSC:

93E11 Filtering in stochastic control theory
93E10 Estimation and detection in stochastic control theory
93E03 Stochastic systems in control theory (general)
90B15 Stochastic network models in operations research
60J75 Jump processes (MSC2010)
90B36 Stochastic scheduling theory in operations research
Full Text: DOI

References:

[1] ZhangW, BranickyM, PhillipsS. Stability of network control systems. IEEE Control Systems Magazine2001; 21(1):84-99.
[2] YangTC. Networked control systems: a brief survey. IET Control Theory and Applications2006; 153(4):403-412.
[3] ZhangJH, LamJ. A probabilistic approach to stability and stabilization of networked control systems. International Journal of Adaptive Control and Signal Processing2015; 29:925-938. · Zbl 1330.93239
[4] ZhangW‐A, YuL, FengG. Stabilization of linear discrete‐time networked control systems via protocol and controller co‐design. International Journal of Robust and Nonlinear Control2015; 25:3072-3085. · Zbl 1327.93333
[5] SunX‐M, LiuK‐Z, WenCY, WangW. Predictive control of nonlinear continuous networked control systems with large time‐varying transmission delays and transmission protocols. Automatica2016; 64:76-85. · Zbl 1329.93065
[6] ZhangD, WangQG, YuL, ShaoQ‐K. \( \mathcal{H}_\infty\) filtering for networked systems with multiple time‐varying transmissions and random packet dropouts. IEEE Transactions on Industrial Informatics2013; 9(3):1705-1716.
[7] WangD, WangJL, WangW. H_∞ controller design of networked control systems with Markov packet dropouts. IEEE Transactions on Systems, Man and Cybernetics: Systems2013; 43(3):689-697.
[8] AntunesD, HespanhaJP, SilvestreC. Stochastic networked control systems with dynamic protocols. Asian Journal of Control2015; 17(1):99-110. · Zbl 1332.93329
[9] HespanhaJP, NaghshtabriziP, XuYG. A survey of recent results in networked control systems. Proceeding of IEEE special issue on Technology of Networked Control Systems2007; 95(1):138-162.
[10] GuptaRA, ChowM‐Y. Networked control system: overview and research trends. IEEE Transactions on Industrial Electronics2010; 57(7):2527-2535.
[11] QiuL, LiSB, XuBG, XuG. \( \mathcal{H}_\infty\) control of networked control systems based on Markov jump unified model. International Journal of Robust and Nonlinear Control2015; 25:2770-2786. · Zbl 1328.93246
[12] PourbabaeeB, MeskinN, KhorasaniK. Sensor fault detection, isolation and identification using multiple‐model‐based hybrid Kalman filter for gas turbine engines. IEEE Transactions on Control Systems Technology2016; 20(4):1184-1200.
[13] MeskinN, KhorasaniK. Actuator fault detection and isolation for a network of unmanned vehicles. IEEE Transactions on Automatic Control2009; 54(4):835-840. · Zbl 1367.93403
[14] HwangI, KimS, KimY, SeahCE. A survey of fault detection, isolation, and reconfiguration methods. IEEE Transactions on Control Systems Technology2010; 18(3):636-653.
[15] SamyI, PostlethwaiteI, GuDW. Survey and application of sensor fault detection and isolation schemes. Control Engineering Practice2011; 19(7):658-674.
[16] SuXJ, ShiP, WuLG, SongYD. Fault detection filtering for nonlinear switched stochastic systems. IEEE Transactions on Automatic Control2016; 61(5):1310-1315. · Zbl 1359.93497
[17] LlanosD, StaroswieckiM, ColomerJ, MeléndezJ. Transmission delays in residual computation. IET Control Theory and Applications2007; 1(5):1471-1476.
[18] WangYQ, DingSX, YeH, WangGZ. A new fault detection scheme for networked control systems subject to uncertain time‐varying delay. IEEE Transactions on Signal Processing2008; 56(10):5258-5268. · Zbl 1390.94584
[19] HeX, WangZD, ZhouDH. Robust fault detection for networked systems with communication delay and data missing. Automatica2009; 45(11):2634-2639. · Zbl 1180.93101
[20] MaoZH, JiangB, ShiP. \( \mathcal{H}_\infty\) fault detection filter design for networked control systems modelled by discrete Markovian jump systems. IET Control Theory and Applications2007; 1(5):1336-1343.
[21] GaoHJ, ChenTW, WangL. Robust fault detection with missing measurements. International Journal of Control2008; 81(5):804-819. · Zbl 1152.93346
[22] WangYQ, YeH, DingSX, WangGZ, ZhouDH. Residual generation and evaluation of networked control systems subject to random packet dropout. Automatica2009; 45(10):2427-2434. · Zbl 1179.93155
[23] ZhangY, WangZD, ZouL, LiuZX. Fault detection filter design for networked multi‐rate systems with fading measurements and randomly occurring faults. IET Control Theory and Applications2016; 10(5):573-581.
[24] LiX‐J, YangG‐H. Fault detection in finite frequency domains for multi‐delay uncertain systems with applications to ground vehicle. Internation Journal of Robust and Nonlinear Control2015; 25(18):3780-3798. · Zbl 1333.90034
[25] WangH, YangG‐H. Integrated fault detection and control for LPV systems. International Journal of Robust and Nonlinear Control2009; 19(3):341-363. · Zbl 1163.93019
[26] LiX‐J, YangG‐H. Fault detection in finite frequency domain for Takagi-Sugeno fuzzy systems with sensor faults. IEEE Transactions on Cybernetics2014; 44(8):1446-1458.
[27] YangHJ, XiaYQ, LiuB. Fault detection for TCS fuzzy discrete systems in finite‐frequency domain. IEEE transactions on systems, Man, and Cybernetics‐Part B: Cybernetics2011; 41(4):911-920.
[28] LongY, YangG‐H. Fault detection for networked control systems subject to quantization and packet dropout. International Journal of Systems Science2013; 44(6):1150-1159. · Zbl 1278.93236
[29] LongY, YangG‐H. Fault detection for a class of networked control systems with finite‐frequency servo inputs and random packet dropouts. IET Control Theory and Applications2012; 6(15):2397-2408.
[30] DačićD, NešićD. Quadratic stabilization of linear networked control systems via simulateneous protocol and controller design. Automatica2007; 43(7):1145-1155. · Zbl 1123.93076
[31] TabbaraM, nešićD. Input‐output stability of networked control systems with stochstic protocols and channels. IEEE Transactions on Automatic Control2008; 53(5):1160-1175. · Zbl 1367.93602
[32] DonkersMCF, HeemelsW. PMH, BernardiniD, BemporadA, ShneerV. Stability analysis of stochastic networked control systems. Automatica2012; 48(5):917-925. · Zbl 1246.93120
[33] IwasakiT, HaraS. Generalized KYP lemma: unified frequency domain inequalities with design applications. IEEE Transactions on Automatic Control2005; 50(1):41-59. · Zbl 1365.93175
[34] YinYY, ShiP, LiuF, LayTeoK. Robust fault detection for discrete‐time stochastic systems with non‐homogeneous jump processes. IET Control Theory and Applications2014; 8(1):1-10. · Zbl 1286.93181
[35] LongY, YangG‐H. Fault detection for a class of nonhomogeneous Markov jump systems based on delta operator approach. Journal of Systems and Control Engineering2012; 227(1):129-141.
[36] FrankMP. Fault diagnosis in dynamic systems using analytical and knowledge‐based redundancy: a survey and some new results. Automatica1990; 26(3):459-474. · Zbl 0713.93052
[37] SiwakositW, SnellSA, HessRA. Robust flight control design decision with handling qualities constraints using scheduled linear dynamic inversion and loop‐shaping. IEEE Transactions on Control Systems Technology2000; 8:483-494.
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