New results on T–S fuzzy sampled-data stabilization for switched chaotic systems with its applications

Vadivel, R.; Sabarathinam, S.; Wu, Yongbao; Chaisena, Kantapon; Gunasekaran, Nallappan

doi:10.1016/j.chaos.2022.112741

Cited by 36 publications

(8 citation statements)

References 38 publications

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“…In practice, the control input of the master system might be nonzero such that the neural network can exhibit various dynamic behaviors, such as stability, 39 exponential stability 40 or chaos. 41,42 In this subsection, the master MNNs have unknown nonzero inputs and the almost surely exponential synchronization can be realized via an adaptive-impulsive hybrid controller.…”

Section: Event-triggered Adaptive-impulsive Controlmentioning

confidence: 99%

“…In practice, the control inputs of the master neural networks may be nonzero such that master SMNNs can exhibit various dynamic behavior, such as stability, 39 exponential stability 40 or chaos. 41,42 But they may have adverse effects on master-slave synchronization. Therefore, an adaptive controller is designed to mitigate the adverse effects of the unknown inputs of the master neural networks.…”

Section: Introductionmentioning

confidence: 99%

“…The selection condition of

\delta

is also determined by the dynamics of SMNNs. Secondly, an event‐triggered adaptive‐impulsive control strategy is designed for master‐slave SMNNs to achieve almost surely exponential synchronization. In practice, the control inputs of the master neural networks may be nonzero such that master SMNNs can exhibit various dynamic behavior, such as stability, 39 exponential stability 40 or chaos 41,42 . But they may have adverse effects on master‐slave synchronization.…”

Section: Introductionmentioning

confidence: 99%

“…and triggering instants are shown in Figure4. When 𝜇 = 0.2, 𝜈 = 0.8, 𝜌 = 0.0071 ≤ 𝜇 𝛽 , Δ = 3, it can be verified that (41),(42) hold. According to(39), there is and the trajectories and triggering instants are shown in Figure5.…”

mentioning

confidence: 97%

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Synchronization of stochastic memristive neural networks via event‐triggered impulsive control

Zhang,

Mu,

2023

Adaptive Control & Signal

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This paper investigates the synchronization problem for master‐slave stochastic memristive neural networks (SMNNs) with time‐delay via event‐triggered impulsive control (ETIC). Firstly, a novel ETIC method is designed for SMNNs to realize quasi‐synchronization in mean square sense. Different from time‐triggered impulsive control (TTIC) in the existing results on SMNNs, the proposed event‐triggered method determines impulsive instants based on the real‐time system states, which can reduce redundant impulses. Compared with the existing ETIC for deterministic memristive neural networks (MNNs), the proposed event‐triggered mechanism (ETM) can exclude Zeno behavior completely by adding the waiting time, when stochastic disturbances occur in MNNs. Secondly, if the master SMNNs have nonzero control inputs, an adaptive‐impulsive hybrid controller with ETM is designed to realize almost surely exponential synchronization. Under the ETM, the number of transmitted events is reduced, then control resources can be saved. Zeno behavior can be excluded in almost sure sense. Ultimately, simulations are presented to illustrate the validity of the obtained results.

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Section: Event-triggered Adaptive-impulsive Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…The selection condition of

\delta

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 97%

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Synchronization of stochastic memristive neural networks via event‐triggered impulsive control

Zhang,

Mu,

2023

Adaptive Control & Signal

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“…In addition, the unique features of this device have stimulated interest in generating nonlinear and chaotic dynamics [ 26 , 27 ]. In recent years, the research and application on chaotic systems have become more and more abundant [ 28 , 29 , 30 , 31 ]. By introducing memristors with different nonlinearities into existing circuits, a large number of circuits based on memristor have been proposed and very fruitful results have been obtained [ 32 , 33 , 34 , 35 , 36 , 37 , 38 ].…”

Section: Introductionmentioning

confidence: 99%

RC Bridge Oscillation Memristor Chaotic Circuit for Electrical and Electronic Technology Extended Simulation Experiment

et al. 2023

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The fourth basic circuit component, the memristor, has been proposed for a long time, but it is not mentioned in the experiment teaching system of Electrical and Electronic Technology. In this paper, an RC bridge oscillation chaotic circuit based on memristor is designed to solve this problem. The dynamical behavior of the circuit system is analyzed using Lyapunov exponents spectrum, bifurcation diagram, phase portrait and Poincaré map. A series of complex dynamical behaviors such as symmetric single-scroll coexistence, asymmetrical single-scroll coexistence, symmetric double-scroll coexistence and asymmetrical limit–cycle coexistence exist in the circuit system. This research plays a critical role in enriching students’ knowledge and improving the experiment teaching system of Electrical and Electronic Technology.

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A novel image encryption scheme based on a new hyperchaotic map

Farah,

Alshammari

2023

Multimed Tools Appl

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New results on T–S fuzzy sampled-data stabilization for switched chaotic systems with its applications

Cited by 36 publications

References 38 publications

Synchronization of stochastic memristive neural networks via event‐triggered impulsive control

Synchronization of stochastic memristive neural networks via event‐triggered impulsive control

RC Bridge Oscillation Memristor Chaotic Circuit for Electrical and Electronic Technology Extended Simulation Experiment

A novel image encryption scheme based on a new hyperchaotic map

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