Synchronization and Antisynchronization Between Two Non-Identical Chua Oscillators via Sliding Mode Control

Mufti, Muhammad Rafiq; Afzal, Humaira; Rehman, Fazal ur; Butt, Qarab Raza; Qureshi, Muhammad Imran

doi:10.1109/access.2018.2865016

Cited by 10 publications

(14 citation statements)

References 51 publications

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“…T has components which are continuously differentiable complex functions of x and φ (x) = φ r (x) + jφ i (x). Definition 2: Consider the systems (1) and (2) and at a given map φ (y) :…”

Section: Some Preliminaries and Definition Of Icgsmentioning

confidence: 99%

Modeling and Inverse Complex Generalized Synchronization and Parameter Identification of Non-Identical Nonlinear Complex Systems Using Adaptive Integral Sliding Mode Control

et al. 2020

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This paper presents the Inverse Complex Generalized Synchronization (ICGS) of non-identical nonlinear complex systems with unknown parameters. Using the philosophy of adaptive integral sliding mode control, an adaptive controller and laws regarding parametric upgradation are designed to realize ICGS and parameter identification of two non-identical chaotic complex systems with respect to a given complex map vector. To employ the control, the error system is transformed into a unique structure containing a nominal part and some unknown terms, which are computed adaptively. Then, the error system is stabilized by using integral sliding mode control. The stabilizing controller for the error system is constructed, which consists of the fractional-order control plus some compensator control. To avoid the chattering phenomenon, smooth continuous compensator control is incorporated instead of traditional discontinuous control. The compensator controller and the adapted law are derived in such a way that the time derivative of a Lyapunov function becomes strictly negative. This scheme is applied to synchronize a Memristor-Based Hyperchaotic Complex (MBHC) Lu system and a Memristor-Based Chaotic Complex (MBCC) Lorenz system, a chaotic complex Chen system and a memristor-based chaotic complex Lorenz system with entirely unknown parameters. The effectiveness and feasibility of the proposed scheme is validated through computer simulation using MATLAB software package.

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“…T has components which are continuously differentiable complex functions of x and φ (x) = φ r (x) + jφ i (x). Definition 2: Consider the systems (1) and (2) and at a given map φ (y) :…”

Section: Some Preliminaries and Definition Of Icgsmentioning

confidence: 99%

Modeling and Inverse Complex Generalized Synchronization and Parameter Identification of Non-Identical Nonlinear Complex Systems Using Adaptive Integral Sliding Mode Control

et al. 2020

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“…Synchronization and control of the Chua system have attracted more attention. Over the past decades, several control approaches have been used to synchronize two different Chua oscillators, such as active control (Mahmoud et al, 2007), adaptive control (Hu et al, 2005), impulsive control (Sun and Zhang, 2004), robust control (Li and Zhao, 2016), sliding mode control (Mufti et al, 2018), robust adaptive state feedback sliding-mode control (Xue et al, 2017), and synchronization via capacitive coupling (Liu et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Control and synchronization for two Chua systems based on intuitionistic fuzzy control scheme: A comparative study

Hamdy

Magdy

Helmy

2021

Transactions of the Institute of Measurement and Control

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This paper presents control and synchronization for two nonlinear chaotic systems in the presence of uncertainties and external disturbances based on an intuitionistic fuzzy control (IFC) scheme. Two classes of Chua and cubic Chua oscillators have been formulated as master and slave respectively. The master and slave systems have different initial conditions and parameters, which leads to the butterfly effect that rules the chaotic systems’ behaviour. IFC scheme is chosen as a different method that has not been used before to control and synchronize Chua and cubic Chua oscillators. The main objective of the IFC scheme is to collect more information about the system and provide flexibility for the controller that increases the robustness of the control system to uncertainties in the structure of the chaotic systems. The stability analysis of the overall system is guaranteed using Routh-Hurwitz and Lyapunov criteria. The simulation results accomplished to evaluate the effectiveness of the proposed control and to demonstrate its reliability to control Chua’s circuit system with a comparative study.

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“…In addition, in 2019, Mandal and Das established chaos-based color image encryption using microcontrollers [5]. In recent decades, various control methods have been reported to synchronize master-slave chaotic systems, such as adaptive control [7], fuzzy control [8], fuzzy-brain emotional-learning networks [9], sliding-mode control [10], and cerebellar model articulation control [11]. However, the majority of these methods are complex, and the controlling performance requires improvement.…”

Section: Introductionmentioning

confidence: 99%

Chaotic Synchronization Using a Self-Evolving Recurrent Interval Type-2 Petri Cerebellar Model Articulation Controller

Lin

Quynh

et al. 2020

Mathematics

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In this manuscript, the synchronization of four-dimensional (4D) chaotic systems with uncertain parameters using a self-evolving recurrent interval type-2 Petri cerebellar model articulation controller is studied. The design of the synchronization control system is comprised of a recurrent interval type-2 Petri cerebellar model articulation controller and a fuzzy compensation controller. The proposed network structure can automatically generate new rules or delete unnecessary rules based on the self-evolving algorithm. Furthermore, the gradient-descent method is applied to adjust the proposed network parameters. Through Lyapunov stability analysis, bounded system stability is guaranteed. Finally, the effectiveness of the proposed controller is illustrated using numerical simulations of 4D chaotic systems.

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Synchronization and Antisynchronization Between Two Non-Identical Chua Oscillators via Sliding Mode Control

Cited by 10 publications

References 51 publications

Modeling and Inverse Complex Generalized Synchronization and Parameter Identification of Non-Identical Nonlinear Complex Systems Using Adaptive Integral Sliding Mode Control

Modeling and Inverse Complex Generalized Synchronization and Parameter Identification of Non-Identical Nonlinear Complex Systems Using Adaptive Integral Sliding Mode Control

Control and synchronization for two Chua systems based on intuitionistic fuzzy control scheme: A comparative study

Chaotic Synchronization Using a Self-Evolving Recurrent Interval Type-2 Petri Cerebellar Model Articulation Controller

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