Control of Memristor-Based Simplest Chaotic Circuit with One-State Controllers

Kizmaz, Hakan; Kocamaz, Uğur Erkin; Uyaroğlu, Yılmaz

doi:10.1142/s0218126619500075

Cited by 16 publications

(5 citation statements)

References 59 publications

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“…In 1990, the OGY method was developed to realize the control of chaos (Ott et al, 1990). Later, researchers developed many methods to control chaotic behavior, such as active (Agrawal et al, 2012), passive (Kuntanapreeda and Sangpet, 2012), time-delay feedback (Ge et al, 2014), linear feedback (Sun et al, 2009), sliding-mode (Li and Liu, 2010), nonlinear control (Boubakir and Labiod, 2022; Din et al, 2021; Kizmaz et al, 2019), and linear quadratic regulator-based control (Alexander et al, 2023). Among the nonlinear control methods, sliding mode control (SMC) has superb advantages, such as being robust against disturbances, sensor noises, and ensuring well-tracking dynamics.…”

Section: Introductionmentioning

confidence: 99%

Fractional-Order sliding mode control of a 4D memristive chaotic system

Gokyildirim

Çalgan

Demirtaş

2023

Journal of Vibration and Control

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Chaotic systems depict complex dynamics, thanks to their nonlinear behaviors. With recent studies on fractional-order nonlinear systems, it is deduced that fractional-order analysis of a chaotic system enriches its dynamic behavior. Therefore, the investigation of the chaotic behavior of a 4D memristive Chen system is aimed in this study by taking the order of the system as fractional. The nonlinear behavior of the system is observed numerically by comparing the fractional-order bifurcation diagrams and Lyapunov Exponents Spectra with 2D phase portraits. Based on these analyses, two different fractional orders (i.e., q = 0.948 and q = 0.97) are determined where the 4D memristive system shows chaotic behavior. Furthermore, a single state fractional-order sliding mode controller (FOSMC) is designed to maintain the states of the fractional-order memristive chaotic system on the equilibrium points. Then, control method results are obtained by both numerical simulations and different illustrative experiments of microcontroller-based realization. As expected, voltage outputs of the microcontroller-based realization are in good agreement with the time series of numerical simulations.

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Section: Introductionmentioning

confidence: 99%

Fractional-Order sliding mode control of a 4D memristive chaotic system

Gokyildirim

Çalgan

Demirtaş

2023

Journal of Vibration and Control

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“…Further, the passive control method based on the Lyapunov function was considered to stabilize a modified memristor chaotic oscillator [130]. Similarly, Kızmaz et al compared the performance of three control methods such as linear feedback control, sliding mode control, and nonlinear control in a memristor-based chaotic oscillator [131]. In another study [92], a fuzzy logic-based proportional integral derivative controller was applied for the chaos control in a memristor-based hyperchaotic system, followed by utilizing an optimal linear quadratic regulator to synchronize the above-mentioned system.…”

Section: Introductionmentioning

confidence: 99%

Minimum variance control of chaos in a hyperchaotic memristor based oscillator using online particle swarm optimization

Setoudeh¹,

Sedigh²

2021

Phys. Scr.

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This paper introduces a new hyperchaotic oscillator base on a new boundary-restricted Hewlett-Packard memristor model. Firstly, the complex system is designed based on a memristor-based hyperchaotic real system, and its properties are analyzed by means of Lyapunov exponents, Lyapunov dimension and phase portraits diagrams. Secondly, a simple feedback control based on the minimum variance control technique is designed to stabilize the hyperchaotic oscillator system, which is one of the new developed approaches for controlling the chaos in high-dimensional hyperchaotic systems. In this method, the time series variance is considered for designing and calculating the state feedback control gain. Furthermore, the state feedback control is designed so that to minimize the variance as a cost function, followed by developing an online optimization technique using the particle swarm optimization method in order to calculate the state feedback control based on the minimum variance strategy. Then, the application of this method is examined on a hyperchaotic memristor-based oscillator. Finally, the sensitivity of the proposed method is evaluated in different initial conditions that greatly influence the hyperchaotic dynamics. Considering that the optimization is online, simulation results show highly good effectiveness of the presented technique in controlling the chaos in high-dimensional hyperchaotic oscillators

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“…Operating frequencies of systems embedded on FPGAs vary between 27-72 MHz. Kizmaz et al [40] carried out the designs and chaos analysis of Memristor-Based Simplest Chaotic system based on DP numerical algorithm in their study. Koyuncu et al [41] performed the Dormand-Prince based chaotic oscillator design with golden proportion balance point on FPGA.…”

Section: Introductionmentioning

confidence: 99%

CCII current conveyor and dormand-prince-based chaotic oscillator designs for secure communication applications

Alçın

Tuna

Pehlivan

et al. 2020

International Advanced Researches and Engineering Journal

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Chaos is one of the important research areas in recent years. The chaotic signal generator is one of the most basic structure in the chaos-based researches and applications. In this study, Sundarapandian-Pehlivan Chaotic Oscillator (SPCO) designs have been implemented in 2 different platforms as analog-based using Second-Generation Current Controlled Current Conveyor (CCII) and FPGA-based with one of the chaotic oscillator that has been presented to the literature namely Sundarapandian-Pehlivan system. The structure used for the design of CCII-based chaotic oscillator and the results obtained from the study have been presented. In the second phase, the design of SPCO has been realized in order to utilize for running in FPGA chips using Dormand-Prince (DP) numeric algorithm. The design has been coded in VHDL using 32-bit IEEE-754-1985 floating point representation. The designed system has been tested by synthesizing it in Xilinx ISE Design Tools program. Then, the test results obtained from DPbased SPCO structure have been presented. In the last phase, the designed system has been synthesized for VIRTEX-7 FPGA. FPGA chip resource consumption values that obtained after the Place-Route process are presented. According to the results, the maximum operating frequency of DP-based SPCO unit on FPGA is obtained as 362.608 MHz. In future studies, the designs of Pseudo Random Number Generator (RNG) and True RNG can be performed using DP-based SPCO unit implemented successfully in this study.

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Control of Memristor-Based Simplest Chaotic Circuit with One-State Controllers

Cited by 16 publications

References 59 publications

Fractional-Order sliding mode control of a 4D memristive chaotic system

Fractional-Order sliding mode control of a 4D memristive chaotic system

Minimum variance control of chaos in a hyperchaotic memristor based oscillator using online particle swarm optimization

CCII current conveyor and dormand-prince-based chaotic oscillator designs for secure communication applications

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