Fixed-time synchronization for discontinuous delayed complex-valued networks with semi-Markovian switching and hybrid couplings via adaptive control
Shujin Liu
School of Science, Yanshan University, Qinhuangdao, China
Search for more papers by this authorCorresponding Author
Huaiqin Wu
School of Science, Yanshan University, Qinhuangdao, China
Correspondence
Huaiqin Wu, School of Science, Yanshan University, Qinhuangdao, Hebei 066001, China.
Email: [email protected]
Search for more papers by this authorJinde Cao
School of Mathematics, Southeast University, Nanjing, China
Search for more papers by this authorShujin Liu
School of Science, Yanshan University, Qinhuangdao, China
Search for more papers by this authorCorresponding Author
Huaiqin Wu
School of Science, Yanshan University, Qinhuangdao, China
Correspondence
Huaiqin Wu, School of Science, Yanshan University, Qinhuangdao, Hebei 066001, China.
Email: [email protected]
Search for more papers by this authorJinde Cao
School of Mathematics, Southeast University, Nanjing, China
Search for more papers by this authorFunding information: High Level Talent Project of Hebei Province of China, C2015003054; Postgraduate Innovation Project of Hebei Province of China, CXZZSS2020041; the Natural Science Foundation of Hebei Province of China, A2018203288
Summary
In this article, the global fixed-time synchronization issue is considered for semi-Markovian switching discontinuous complex-valued dynamical networks (CVDNs) with hybrid couplings and time-varying delays, in which CVDNs are not divided into two real value systems, contrary to existing literature. First, a new fixed-time convergence principle for complex-valued nonlinear system with semi-Markovian switching is developed. Second, to realize the fixed-time synchronization, the state feedback controller with integral term and adaptive controller are designed, respectively. Under the complex-valued differential inclusions framework, by utilizing Lyapunov-Krasovskii functional method and inequality analysis technique, the global fixed-time synchronization conditions are addressed in terms of linear matrix inequalities. Finally, two numerical simulations are given to illustrate the validity of the presented theoretical results.
REFERENCES
- 1Guo R, Zhang Z, Liu X. Existence, uniqueness, and exponential stability analysis for complex-valued memristor-based BAM neural networks with time delays. Appl Math Comput. 2017; 311: 100-117.
- 2Wang L, Song Q, Liu Y, Zhao Z, Alsaadi FE. Global asymptotic stability of impulsive fractional-order complex-valued neural networks with time delay. Neurocomputing. 2017; 243: 49-59.
- 3Arima Y, Hirose A. Performance dependence on system parameters in millimeter-wave active imaging based on complex-valued neural networks to classify complex texture. IEEE Access. 2017; 5: 22927-22939.
- 4Wang X, Wu H, Cao J. Global leader-following consensus in finite time for fractional-order multi-agent systems with discontinuous inherent dynamics subject to nonlinear growth. Nonlinear Anal Hybrid Syst. 2020; 37: 10088. https://doi.org/10.1016/j.nahs.2020.10088.
- 5Wu X, Feng J, Zhe N. Pinning complex-valued complex network via aperiodically intermittent control. Neurocomputing. 2018; 305: 70-77.
- 6Soletta JH, Farfĺćn FD, Albarracĺłn AL, Pizĺć AG, Lucianna FA, Felice CJ. Cloud-assisted secure biometric identification with sub-linear search efficiency. Soft Comput. 2020; 24: 5885-5896.
- 7Nitta T. Solving the XOR problem and the detection of symmetry using a single complex-valued neuron. Neural Netw. 2003; 16: 1101-1105.
- 8Ning CZ, Haken H. Quasiperiodicity involving twin oscillations in the complex lorenz equations describing a detuned laser. Zeitschrift Fur Physik B. 1990; 81: 457-461.
10.1007/BF01390829 Google Scholar
- 9Yang CD. A new hydrodynamic formulation of complex-valued quantum mechanics. Chaos Soliton Fract. 2009; 42: 453-468.
- 10Tanzosh JP, Stone HA. Transverse motion of a disk through a rotating viscous fluid. J Fluid Mech. 2006; 301: 295-324.
- 11Xu X, Zhang J, Shi J. Dynamical behaviour analysis of delayed complex-valued neural networks with impulsive effect. Int J Syst Sci. 2017; 48: 686-694.
- 12Wang Z, Guo Z, Huang L, Liu X. Dynamical behavior of complex-valued hopfield neural networks with discontinuous activation functions. Neural Process Lett. 2017; 45: 1039-1061.
- 13Ieee AWM, Hanazawa T, Hinton G, Ieee KSM, Lang KJ. Phoneme recognition using time-delay neural networks. Read Speech Recog. 1989; 37: 328-339.
- 14Hampshire JB, Waibel AH. A novel objective function for improved phoneme recognition using time-delay neural networks. IEEE Trans Neural Netw. 1990; 1: 216-228.
- 15Ranjan P, Abed EH, La RJ. Communication delay and instability in rate-controlled networks. IEEE Conf Decis Control. 2003; 36: 165-176.
- 16Lan Z, Yang X, Chen X, Feng J. Exponential synchronization of complex-valued complex networks with time-varying delays and stochastic perturbations via time-delayed impulsive control. Appl Math Comput. 2017; 306: 22-30.
- 17Peng X, Wu H, Cao J. Global non-fragile synchronization in finite time for fractional-order discontinuous neural networks with nonlinear growth activations. IEEE Trans Neural Netw Learn Syst. 2019; 30: 2123-2137.
- 18Wu H, Wang L, Niu P. Global projective synchronization in finite time of nonidentical fractional order neural networks based on sliding mode control strategy. Neurocomputing. 2017; 235: 264-273.
- 19Peng X, Wu H. Non-fragile robust finite-time stabilization and H∞ performance analysis for fractional-order delayed neural networks with discontinuous activations under the asynchronous switching. Neural Comput Appl. 2020; 32: 4045-4071.
- 20Li X, Fang J, Li H. Master-slave exponential synchronization of delayed complex-valued memristor-based neural networks via impulsive control. Neural Netw. 2017; 93: 165-175.
- 21Chao Z, Zhang W, Yang X, Chen X, Feng J. Finite-time synchronization of complex-valued neural networks with mixed delays and uncertain perturbations. Neural Process Lett. 2017; 46: 271-291.
- 22Zhang H, Wang X. Complex projective synchronization of complex-valued neural network with structure identification. J Frankl Inst. 2017; 354: 5011-5025.
- 23Jia Y, Wu H, Cao J. Non-fragile robust finite-time synchronization for fractional-order discontinuous complex networks with multi-weights and uncertain couolping under asynchronous switching. Appl Math Comput. 2020; 370:124929. https://doi.org/10.1016/j.amc.2019.124929.
- 24Ding K, Zhu Q, Liu L. Extended dissipativity stabilization and synchronization of uncertain stochastic reaction-diffusion neural networks via intermittent non-fragile control. J Frankl Inst-Eng Appl Math. 2019; 356: 11690-11715.
- 25Song Y, Sun W. Adaptive aynchronization of stochastic memristor-based neural networks with mixed delays. Neural Process Lett. 2017; 46: 969-990.
- 26Ding K, Zhu Q. H-infinity synchronization of uncertain stochastic time-varying delay systems with exogenous disturbance via intermittent control. Chaos Soliton Fract. 2019; 127: 244-256.
- 27Polyakov A. Nonlinear feedback design for fixed-time stabilization of linear control systems. IEEE Trans Autom Control. 2012; 57: 2106-2110.
- 28Polyakov A, Efimov D, Perruquetti W. Finite-time and fixed-time stabilization: implicit Lyapunov function approach. Automatica. 2015; 51: 332-340.
- 29Khanzadeh A, Pourgholi M. Fixed-time sliding mode controller design for synchronization of complex dynamical networks. Nonlinear Dyn. 2017; 88: 2637-2649.
- 30Hui Z, Li L, Peng H, Xiao J, Yang Y, Zheng M. Fixed-time synchronization of multi-links complex network. Modern Phys Lett B. 2017; 31: 1-24.
- 31Liu X, Ho DWC, Qiang S, Xu W. Finite/fixed-time pinning synchronization of complex networks with stochastic disturbances. IEEE Trans Cybern. 2018; 99: 2398-2403.
- 32Yang X, Lam J, Daniel WC. Fixed-Time Synchronization of complex networks With impulsive effects via nonchattering control. IEEE Trans Autom Control. 2017; 62: 5511-5521.
- 33Hu C, Yu J, Chen Z. Fixed-time stability of dynamical systems and fixed-time synchronization of coupled discontinuous neural networks. Neural Netw. 2017; 89: 74-83.
- 34Kong F, Zhu Q, Sakthive R. Finite-time and fixed-time synchronization control of fuzzy Cohen-Grossberg neural networks. Fuzzy Sets Syst. 2020; 394: 87-109.
- 35Wang Z, Wu H. Global synchronization in fixed time for semi-Markovian switching complex dynamical networks with hybrid couplings and time-varying delays. Nonlinear Dyn. 2019; 95: 2031-2062.
- 36Zhao W, Wu H. Fixed-time synchronization of semi-Markovian jumping neural networks with time-varying delays. Adv Differ Equat. 2018; 2018: 213. http://doi.org/10.1186/s13662-018-1666-z.
- 37Sivaranjani K, Rakkiyappan R, Joo YH. Event triggered reliable synchronization of semi-Markovian jumping complex dynamical networks via generalized integral inequalities. J Frankl Inst. 2018; 355: 3691-3716.
- 38Lee TH, Qian M, Xu S, Ju HP. Pinning control for cluster synchronisation of complex dynamical networks with semi-Markovian jump topology. Int J Control. 2015; 88: 1223-1235.
- 39Liu M, Wu H. Stochastic finite-time synchronization for discontinuous semi-Markovian switching neural networks with time delays and noise disturbance. Neurocomputing. 2018; 310: 246-264.
- 40Wang B, Zhu Q. Stability analysis of semi-Markov switched stochastic systems. Automatica. 2018; 94: 72-80.
- 41Wang B, Zhu Q. Asymptotic stability in distribution of stochastic systems with semi-Markovian switching. Int J Control. 2019; 92: 1314-1324.
- 42Wei Y, Park JH, Qiu J, Wu L, Jung HY. Sliding mode control for semi-Markovian jump systems via output feedback. Automatica. 2017; 81: 133-141.
- 43Wei Y, Park JH, Karimi HR. Improved stability and stabilization results for stochastic synchronization of continuous-time semi-Markovian jump neural networks with time-varying delay. IEEE Trans Neural Netw Learn Syst. 2018; 29: 2488-2501.
- 44Wu Z, Chen G, Fu X. Synchronization of a network coupled with complex-variable chaotic systems. Chaos. 2017; 22: 023127. https://doi.org/10.1063/1.4717525.
- 45Liu X, Yu X, Zhou X. Finite-time H∞ control for linear systems with semi-Markovian switching. Nonlinear Dyn. 2016; 85: 2297-2308.
- 46Chen C, Li L, Peng H, Yang Y, Mi L, Qiu B. Fixed-time projective synchronization of memristive neural networks with discrete delay. Phys A Stat Mech Appl. 2019; 534:122248. https://doi.org/10.1016/j.physa.2019.122248.
- 47Yaz EE. Linear matrix inequalities in system and control theory. Proc IEEE. 1994; 86: 2473-2474.
10.1109/JPROC.1998.735454 Google Scholar
- 48Khastan A, Rosana R. On linear fuzzy differential equations by differential inclusions' approach. Fuzzy Sets Syst. 2020; 387: 49-67.
- 49Wang H, Zhu Q. Finite-time stabilization of high-order stochastic nonlinear systems in strict-feedback form. Automatica. 2015; 54: 284-291.
- 50Zhu Q. Stabilization of stochastic nonlinear delay systems with exogenous disturbances and the event-triggered feedback control. IEEE Trans Autom Control. 2019; 64: 3764-3771.
- 51Liu M, Wu H, Zhao W. Event-triggered stochastic synchronization in finite time for delayed semi-Markovian jump neural networks with discontinuous activations. Comput Appl Math. 2020; 39: 118. https://doi.org/10.1007/s40314-020-01146-2.
- 52Zhu Q. Stability analysis of stochastic delay differential equations with Levy noise. Syst Control Lett. 2018; 118: 62-68.