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17.06.2019 | Methodologies and Application

Extended dissipativity and event-triggered synchronization for T–S fuzzy Markovian jumping delayed stochastic neural networks with leakage delays via fault-tolerant control

verfasst von: M. Syed Ali, R. Vadivel, Ahmed Alsaedi, Bashir Ahmad

Erschienen in: Soft Computing | Ausgabe 5/2020

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Abstract

This paper concentrates on the extended dissipativity and event-triggered synchronization for T–S fuzzy Markovian jumping delayed stochastic neural networks with leakage delays and fault-tolerant control. We present an event-triggered communication scheme, which utilizes the effect of transmission delay with different failure rates. After giving a foundation to the stochastic model, the paper establishes some fundamental results on quadratically stable and extended dissipativity utilizing the Lyapunov functional, free-weight matrices, as well as the relationship between time-varying delay and leakage delays. The explicit expression of the desired controller gains and event-triggered parameters can be obtained by solving the established LMIs. The novel extended dissipative inequality contains several weighting matrices, by converting the weighting matrices in a new performance index, and the extended dissipativity will be degraded to the \(H_{\infty }\) performance, \(L_2-L_{\infty }\) performance, passivity and dissipativity, respectively. Finally, interesting numerical examples are given to show the effectiveness of the theoretical results.

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Ali MS, Saravanakumar R, Ahn CK, Karimi HR (2017a) Stochastic \(H_{\infty }\) filtering for neural networks with leakage delay and mixed time-varying delays. Inform Sci 388–389:118–134MATH

Ali MS, Gunasekaran N, Zhu Q (2017b) State estimation of T–S fuzzy delayed neural networks with Markovian jumping parameters using sampled-data control. Fuzzy Sets Syst 306:87–104MathSciNetMATH

Arik S (2014) An improved robust stability result for uncertain neural networks with multiple time delays. Neural Netw 54:1–10MATH

Balasubramaniam P, Ali MS, Arik S (2010) Global asymptotic stability of stochastic fuzzy cellular neural networks with multiple time-varying delays. Expert Syst Appl 37:7737–7744

Cichocki A, Unbehauen R (1993) Neural networks for optimization and signal processing. Wiley, ChichesterMATH

Fang S, Jiang M, Wang X (2009) Exponential convergence estimates for neural networks with discrete and distributed delays. Nonlinear Anal Real World Appl 10:702–714MathSciNetMATH

Feng Z, Lam J (2011) Stability and dissipativity analysis of distributed delay cellular neural networks. IEEE Trans Neural Netw 22:976–981

Feng Z, Shi P (2017) Admissibilization of singular interval-valued fuzzy systems. IEEE Trans Fuzzy Syst 25:1765–1776

Gopalsamy K (1992) Stability and oscillations in delay differential equations of population dynamics. Kluwer Academic Publishers, DordrechtMATH

Gopalsamy K (2007) Leakage delays in BAM. J Math Anal Appl 325:1117–1132MathSciNetMATH

Guan W, Liu F (2016) Finite-time dissipative control for singular T–S fuzzy Markovian jump systems under actuator saturation with partly unknown transition rates. Neurocomputing 207:60–70

Hu S, Yin X, Zhang Y, Tian EG (2012) Event-triggered guaranteed cost control for uncertain discrete-time networked control systems with time-varying transmission delays. IET Control Theory Appl 6:2793–2804MathSciNet

Jeltsema D, Scherpen JMA (2004) Tuning of passivity-preserving controllers for switched-mode power converters. IEEE Trans Autom Control 48:1333–1344MathSciNetMATH

Kao YG, Wang CH, Xie J, Karimi HR, Li W (2015) \(H_{\infty }\) sliding mode control for uncertain neutral-type stochastic systems with Markovian jumping parameters. Inform Sci 314:200–211MathSciNetMATH

Kovacic M (1991) Markovian neural networks. Biol Cybern 64:337–342MathSciNetMATH

Lee TH, Park MJ, Park JH, Kwon OM, Lee SM (2014) Extended dissipative analysis for neural networks with time-varying delays. IEEE Trans Neural Netw Learn Syst 25:1936–1941

Li X, Cao J (2010) Delay-dependent stability of neural networks of neutral type with time delay in the leakage term. Nonlinearity 23:1709–1726MathSciNetMATH

Li T, Luo Q, Sun CY, Zhang BY (2009) Exponential stability of recurrent neural networks with time-varying discrete and distributed delays. Nonlinear Anal Real World Appl 10:2581–2589MathSciNetMATH

Li H, Gao H, Shi P, Zhao X (2014) Fault-tolerant control of Markovian jump stochastic systems via the augmented sliding mode observer approach. Automatica 50:1825–1834MathSciNetMATH

Li B, Wang Z, Ma L (2018) An event-triggered pinning control approach to synchronization of discrete-time stochastic complex dynamical networks. IEEE Trans Neural Netw Learn Syst 29:5812–5822MathSciNet

Li W, Wang Z, Liu Q, Guo L (2019) An information aware event-triggered scheme for particle filter based remote state estimation. Automatica 103:151–158MathSciNetMATH

Liu H, Wang Z, Shen B, Liu X (2018) Event-triggered \(H_{\infty }\) state estimation for delayed stochastic memristive neural networks with missing measurements: the discrete time case. IEEE Trans Neural Netw Learn Syst 29:3726–3737MathSciNet

Ma H, Li H, Liang H, Dong G (2019) Adaptive fuzzy event-triggered control for stochastic nonlinear systems with full state constraints and actuator faults. IEEE Trans Fuzzy Syst. https://doi.org/10.1109/TFUZZ.2019.2896843 CrossRef

Mao X (1997) Stochastic differential equations with their applications. Horwood, ChichesterMATH

Mao Z, Jiang B, Shi P (2007) \(H_{\infty }\) fault detection filter design for networked control systems modelled by discrete Markovian jump systems. IET Control Theory Appl 1:1336–1343MathSciNet

Niu Y, Wang X, Lu J (2004) Dissipative-based adaptive neural control for nonlinear systems. J Control Theory Appl 2:126–130MathSciNetMATH

Pecora LM, Carroll TL (1990) Synchronization in chaotic systems. Phys Rev Lett 64:821–824MathSciNetMATH

Peng C, Yang TC (2013) Event-triggered communication and \(H_{\infty }\) control co-design for networked control systems. Automatica 49:1326–1332MathSciNetMATH

Qiu J, Tian H, Lu Q, Gao H (2013) Nonsynchronized robust filtering design for continuous-time T–S fuzzy affine dynamic systems based on piecewise Lyapunov functions. IEEE Trans Cybern 43:1755–1766

Sakthivel R, Selvaraj P, Mathiyalagan K, Park JH (2015a) Robust fault-tolerant \(H_{\infty }\) control for offshore steel jacket platforms via sampled-data approach. J Franklin Inst 352:2259–2279MathSciNetMATH

Sakthivel R, Selvi S, Mathiyalagan K (2015b) Fault-tolerant sampled-data control of flexible spacecraft with probabilistic time delays. Nonlinear Dyn 79:1835–1846MATH

Selvaraj P, Sakthivel R, Marshal Anthoni S, Rathika M, Y.Cheol M (2016) Dissipative sampled-data control of uncertain nonlinear systems with time-varying delays. Complexity 21:142–154MathSciNet

Senan S, Ali MS, Vadivel R, Arik S (2017) Decentralized event-triggered synchronization of uncertain Markovian jumping neutral-type neural networks with mixed delays. Neural Netw 86:32–41MATH

Sheng L, Wang Z, Zou L, Alsaadi FE (2017) Event-based \(H_{\infty }\) state estimation for time-varying stochastic dynamical networks with state- and disturbance-dependent noises. IEEE Trans Neural Netw Learn Syst 28:2382–2394MathSciNet

Shu Z, Lam J (2008) Global exponential estimates of stochastic interval neural networks with discrete and distributed delays. Neurocomputing 71:2950–2963

Syed AM (2015) Stability of Markovian jumping recurrent neural networks with discrete and distributed time varying delays. Neurocomputing 149:1280–1285

Takagi T, Sugeno M (1985) Fuzzy identification of systems and its applications to modeling and control. IEEE Trans Syst Man Cybern 15:116–132MATH

Tan Y, Du D, Qi Q (2017) State estimation for Markovian jump systems with an event-triggered communication scheme. Circuits Syst Signal Process 36:2–24MathSciNetMATH

Tong D, Zhou W, Zhou X, Yang J, Xu Y (2015) Exponential synchronization for stochastic neural networks with multi-delayed and Markovian switching via adaptive feedback control. Commun Nonlinear Sci Numer Simul 29:359–371MathSciNet

Tong D, Rao P, Chen Q, Ogorzalek MJ, Li X (2018) Exponential synchronization and phase locking of a multilayer Kuramoto-oscillator system with a pacemaker. Neurocomputing 308:129–137

Wang S, Feng J, Zhang H (2014) Robust fault tolerant control for a class of networked control systems with state delay and stochastic actuator failures. Int J Adapt Control Signal Process 28:798–811MATH

Wang H, Shi P, Lim C, Xue Q (2015) Event-triggered control for networked Markovian jump systems. Int J Robust Nonlinear 25:3422–3438MathSciNetMATH

Wei H, Li R, Chen C, Tu Z (2016) Extended dissipative analysis for memristive neural networks with two additive time-varying delay components. Neurocomputing 216:429–438

Wen S, Zeng Z, Chen MZQ, Huang T (2017) Synchronization of switched neural networks with communication delays via the event-triggered control. IEEE Trans Neural Netw Learn Syst 28:2334–2343MathSciNet

Wu ZG, Lam J, Su H, Chu J (2012) Stability and dissipativity analysis of static neural networks with time delay. IEEE Trans Neural Netw Learn Syst 23:199–210

Xiao J, Li Y, Zhong S, Xu F (2016) Extended dissipative state estimation for memristive neural networks with time-varying delay. ISA Trans 64:113–128

Xu C, Tong D, Chen Q, Zhou W, Shi P (2019) Exponential stability of Markovian jumping systems via adaptive sliding mode control. IEEE Trans Syst Man Cybern Syst. https://doi.org/10.1109/TSMC.2018.2884565 CrossRef

Yue D, Tian E, Zhang Y, Peng C (2009) Delay-distribution dependent stability and stabilization of T–S fuzzy systems with probabilistic interval delay. IEEE Trans Syst Man Cybern Syst Part B Cybern 39:503–516

Zeng HB, Park JH, Zhang CF, Wang W (2015a) Stability and dissipativity analysis of static neural networks with interval time-varying delay. J Franklin Inst 352:1284–1295MathSciNetMATH

Zeng HB, He Y, Shi P, Wu M, Xiao SP (2015b) Dissipativity analysis of neural networks with time-varying delays. Neurocomputing 168:741–746

Zeng N, Zhang H, Liu W, Liang J, Alsaadi FE (2017) A switching delayed PSO optimized extreme learning machine for short-term load forecasting. Neurocomputing 240:175–182

Zeng N, Qiu H, Wang Z, Liu W, Li Y (2018) A new switching-delayed-PSO-based optimized SVM algorithm for diagnosis of Alzheimer’s disease. Neurocomputing 320:195–202

Zhang XM, Han QL (2014) Event-triggered dynamic output feedback control for networked control systems. IET Control Theory Appl 8:226–234MathSciNet

Zhang J, Peng C (2016) Synchronization of master-slave neural networks with a decentralized event triggered communication scheme. Neurocomputing 173:1824–1831

Zhang B, Zheng WX, Xu S (2013) Filtering of Markovian jump delay systems based on a new performance index. IEEE Trans Circuits Syst I(60):1250–1263MathSciNet

Zheng C, Zhang X, Wang Z (2015) Mode-dependent stochastic stability criteria of fuzzy Markovian jumping neural networks with mixed delays. ISA Trans 56:8–17

Zhu Q, Cao J (2010) Stability analysis for stochastic neural networks of neutral-type with both Markovian jump parameters and mixed time delays. Neurocomputing 73:2671–2680

Zhu Q, Cao J, Hayat T, Alsaadi F (2013) Robust stability of Markovian jump stochastic neural networks with time delays in the leakage terms. Neural Process Lett 41:1–27

Titel: Extended dissipativity and event-triggered synchronization for T–S fuzzy Markovian jumping delayed stochastic neural networks with leakage delays via fault-tolerant control
verfasst von: M. Syed Ali
R. Vadivel
Ahmed Alsaedi
Bashir Ahmad
Publikationsdatum: 17.06.2019
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 5/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-019-04136-7

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