Switched Fuzzy Sampled-Data Control of Chaotic Systems With Input Constraints

Chen, Yunjun; Cao, Qiuxia; Zhu, Zhenyu; Wang, Zhangang; Zhao, Zhanshan

doi:10.1109/access.2021.3066402

Cited by 10 publications

(1 citation statement)

References 23 publications

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“…It is more sensitive to its setup conditions, such as control parameters and initial values (seeds). As a result, a small change in its control parameters or seed causes a significant change in the chaotic outputs [14]. These features are linked to those of a good cipher in cryptography, like diffusion and confusion.…”

Section: Chaotic Systemsmentioning

confidence: 99%

Combined Chebyshev and logistic maps to generate pseudorandom number generator for internet of things

Jassim

Farhan

2022

IJECE

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<span>Sensitive data exchanging among things over the Internet must be protected by a powerful cryptographic system. Conventional cryptographic such as advanced encryption standard (AES), and respiratory sinus arrhythmia (RSA) are not effective enough to protect internet of things (IoT) because of certain inveterate IoT properties like limited memory, computation, and bandwidth. Nowadays, chaotic maps with high sensitivity to initial conditions, strong ergodicity, and non-periodicity have been widely used in IoT security applications. So, it is suitable for IoT. Also, in a stream cipher method, the user needs to deliver the keystream to all clients in advance. Consequently, this paper proposed a method to solve the keys distribution problem based on combine both Chebyshev and logistic maps techniques as well as a master key to generate a random key. The suggested method was compared with the other stream cipher algorithms (Chacha20, RC4, Salsa20) by utilizing the same plaintext and master key as input parameters and the results were successful in the statistical national institute of standards and technology (NIST) test. Simultaneously, the suggestion was evaluated through different evaluation methods like statistical NIST test, histogram, Shannon entropy, correlation coefficient analysis, keyspace and key sensitivity, and others. All mentioned tests are passed successfully. Therefore, the suggested approach was proved it is effective in security issues.</span>

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Section: Chaotic Systemsmentioning

confidence: 99%

Combined Chebyshev and logistic maps to generate pseudorandom number generator for internet of things

Jassim

Farhan

2022

IJECE

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Reliable Finite‐Time Control for Nonlinear Chaotic Semi‐Markov Jump Systems With Incomplete Transition Rates

Abinandhitha,

Sakthivel,

Tatar

et al. 2024

Adaptive Control & Signal

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This article studies the finite‐time control problem for a class of nonlinear chaotic semi‐Markov jump systems with incomplete transition rates described by the T‐S fuzzy model approach. As a means to depict the dynamical properties pertaining to the examined system, parametric uncertainties, faults, external disturbances and input saturation are taken into consideration. The foremost objective of this study is to come up with a composite control mechanism that effectively rejects and attenuates the repercussions of faults and disturbances. In particular, we primarily built a disturbance observer in order to obtain a precise estimation of the external disturbances. After which, the fault diagnosis observer is designated to effectively estimate the faults. Specifically, a composite reliable control mechanism is developed by fusing the output of the constructed observers with the mode‐dependent fuzzy‐rule based state feedback controller. By employing suitable Lyapunov functions in conjunction with the linear matrix inequality technique, a set of mode‐dependent conditions is derived to ensure the finite‐time stochastic boundedness of the underlying closed‐loop and estimation error systems. Following this, the anticipated controller and observer gain matrices are elicited by resolving the established linear matrix inequalities. Thereafter, intending to ascertain the efficacy and usefulness of accrued theoretical findings, simulation results performed on Chua's circuit system is endowed.

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Dynamics analysis and fractional-order nonlinearity system via memristor-based Chua oscillator

Sabarathinam,

Papov,

Wang

et al. 2023

Pramana - J Phys

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Switched Fuzzy Sampled-Data Control of Chaotic Systems With Input Constraints

Cited by 10 publications

References 23 publications

Combined Chebyshev and logistic maps to generate pseudorandom number generator for internet of things

Combined Chebyshev and logistic maps to generate pseudorandom number generator for internet of things

Reliable Finite‐Time Control for Nonlinear Chaotic Semi‐Markov Jump Systems With Incomplete Transition Rates

Dynamics analysis and fractional-order nonlinearity system via memristor-based Chua oscillator

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