Synchronisation of 6D hyper-chaotic system with unknown parameters in the presence of disturbance and parametric uncertainty with unknown bounds

Sabaghian, Alireza; Balochian, Saeed; Yaghoobi, Mahdi

doi:10.1080/09540091.2020.1723491

Cited by 17 publications

(8 citation statements)

References 31 publications

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“…It should be mentioned that synchronization of 6D chaotic systems in the presence of time-delay has less been studied in previous studies. Thus, this paper is compared with Sabaghian et al (2020) in which there is no time delay.…”

Section: Simulationmentioning

confidence: 99%

“…In Sabaghian and Balochian (2022), synchronization of two 6D hyper-chaotic systems in the presence of unknown uncertainty and disturbance using adaptive sliding mode control with two control signals has been investigated. In Sabaghian et al (2020), synchronization of two 6D hyper-chaotic systems in the presence of unknown parametric uncertainty and disturbance and unknown system parameters with adaptive sliding mode control with six control signals has been investigated.…”

Section: Introductionmentioning

confidence: 99%

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Fault-tolerant complete synchronization of integer and fractional derivative 6D hyper-chaotic systems with unknown time delay

Sabaghian

Balochian

2022

Transactions of the Institute of Measurement and Control

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In this study, synchronization of two 6D hyper-chaotic systems in the presence of bounded disturbance and uncertainty with unknown bounds and time delay for integer-order and fractional-order systems is investigated. In the first step of the selected control approach, a proper sliding surface is defined for synchronization of two hyper-chaotic systems, a proper active control is considered, and proper adaptive laws are used to estimate the uncertainty bounds, the unknown disturbance, and unknown time delay of the master and slave systems. The stability of the closed-loop control system is proved using the Lyapunov theorem. Simulation results using MATLAB verify desired performance of the proposed controllers in the presence of unknown disturbance, uncertainty, and time delay.

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Section: Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fault-tolerant complete synchronization of integer and fractional derivative 6D hyper-chaotic systems with unknown time delay

Sabaghian

Balochian

2022

Transactions of the Institute of Measurement and Control

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“…Finally, stability of the designed control scheme is proved using the Lyapunov stability method. In [64], ASMC method is proposed for chaos-based synchronization of 6-D drive-response nonlinear systems in the presence of unknown parameters and external disturbance in the response system. Firstly, two 6-D integer-order drive-response systems in the presence of unknown parameters and external disturbance signal in the response system are designed.…”

Section: Introductionmentioning

confidence: 99%

Finite-time synchronization of a new five-dimensional hyper-chaotic system via terminal sliding mode control

et al. 2023

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prove that the introduced new 5-D hyper-chaotic system has complex and nonlinear behaviors. Next, the work describes Fast Terminal Sliding Mode Control (FTSMC) scheme for the control and finite-time fast synchronization of the novel 5-D nonlinear hyper-chaotic system. Proof of stability for both phases has been done for the new controller with the Lyapunov stability theory. For the synchronization, both master-slave subsystems are perturbed by different parameter and model uncertainties. Both steps of the Sliding Mode Controller (SMC) have chaos-based fast convergence properties. Subsequently, it has been shown that the state paths of both master-slave systems can reach each other in a limited-time. One of the features of the novel controller in this paper, is high performance and finite-time stability of the terminal sliding surface due to derivative error and error. Finally, using the MATLAB simulation, the results are confirmed for the new hyper-chaotic system.

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“…It is possible to improve existing estimation further, using popular prediction models based on various artificial intelligence tools and the COSMIC FP method. Artificial neural networks (ANN) have proven to be a compelling idea for prediction because they can transmit information to certain elements modified by appropriate transformations and passed on to other elements (Kheyrinataj & Nazemi, 2020;Meng et al, 2017;Moosavi & Bardsiri, 2017;Sabaghian et al, 2020). The input values of the ANN represent the independent variables based on which the prediction is made.…”

Section: Introductionmentioning

confidence: 99%

COSMIC FP method in software development estimation using artificial neural networks based on orthogonal arrays

Ranković

Ivanović

et al. 2021

Connection Science

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This paper proposes a new, improved COmmon Software Measurement International Consortium function point (COSMIC FP) method that uses Artificial Neural Network (ANN) architectures based on Taguchi's Orthogonal Array to estimate software development effort. The minimum magnitude relative error (MRE) to evaluate these architectures considering the cost effect function, the type of data used in the training, testing, and validation of the proposed models, was used. Applying the fuzzification and clustering method to obtain seven different datasets, we would like to achieve excellent reliability and accuracy of the obtained results. Besides examining the influence of four input values, we aim to reduce the risks of potential errors, increase the coverage of a wide range of different projects and increase the efficiency and success of completing many various software projects. The main contributions of our work are as follows: the influence of four input values of the COSMIC FP method on the change of mean (MRE), development of two simple ANN architectures, the attainment of a small number of performed iterations in software effort estimation (less than 7), reduced software effort estimation time, the use of different values of the International Software Benchmarking Standards Group and other datasets used in the experiment.

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Synchronisation of 6D hyper-chaotic system with unknown parameters in the presence of disturbance and parametric uncertainty with unknown bounds

Cited by 17 publications

References 31 publications

Fault-tolerant complete synchronization of integer and fractional derivative 6D hyper-chaotic systems with unknown time delay

Fault-tolerant complete synchronization of integer and fractional derivative 6D hyper-chaotic systems with unknown time delay

Finite-time synchronization of a new five-dimensional hyper-chaotic system via terminal sliding mode control

COSMIC FP method in software development estimation using artificial neural networks based on orthogonal arrays

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