Fuzzy Adaptive Time-Delay Feedback Controlling Chaos in Buck Converter

Li, Zicheng; Yuan, Yuan; Wang, Hou-Neng

doi:10.1109/ccdc49329.2020.9164013

Cited by 4 publications

(6 citation statements)

References 15 publications

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“…These characteristics can just meet the requirements of encryption. Therefore, chaos has been extensively applied in numerous realms, such as chaos control (Tian et al (2021); Li et al (2020)), chaotic spread spectrum communication (Yuan et al (2021); Xiao et al (2018)), secure communication (Zhao et al (2020); He et al (2020)), chaos optimization (Shi et al (2008))and so on. Besides, the application of chaos in cryptography is not difficulity to be realized.…”

Section: Figure 1 the Block Diagram Of Distributed Power Energy Systemmentioning

confidence: 99%

Data encryption based on 7D complex chaotic system with cubic memristor for smart grid

et al. 2022

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The information security has an irreplaceable position in the smart grid (SG). In order to avoid the malicious attack and ensure the information security, the cryptographic techniques are essential. This paper focuses on the encryption techniques to ensure the information security of SG. Firstly, an unusual 7-dimensional complex chaotic system (7D-CCS) combined with the cubic memristor is introduced. Besides its phase portraits, Lyapunov exponent, 0–1 test, complexity, and bifurcation diagram are investigated. Then, with the proposed 7D-CCS, we design a data encryption algorithm to ensure the encryption security. Finally, the data and monitoring images in SG are encrypted by the designed encryption scheme. Besides, the encryption performance is given in detailed. The experimental results show that the proposed encryption scheme has quite good encryption performance. Therefore, it can ensure the information security of SG.

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Section: Figure 1 the Block Diagram Of Distributed Power Energy Systemmentioning

confidence: 99%

Data encryption based on 7D complex chaotic system with cubic memristor for smart grid

et al. 2022

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“…, which is Ppv from 1000 W→900 W, the measured DC-link voltage VBus variable waveform is shown in Figure 10, and the steady-state voltage is at 173 V. 17) and ( 18), respectively. (g) a = 26.88 and b = 537.7 can be estimated from Equation (17); therefore, the transfer function G p (s) of the bidirectional soft-switching converter can be written as:…”

Section: Time(ms) 50msmentioning

confidence: 99%

“…(f) The steady-state response of power step change can be obtained against DC-link voltage from Figure 10 and calculate = 0.056 and Kpv = 0.00967 from Equation ( 18). (g) a = 26.88 and b = 537.7 can be estimated from Equation (17); therefore, the transfer function Gp(s) of the bidirectional soft-switching converter can be written as:…”

Section: Quantitative Design Of the Voltage Controllermentioning

confidence: 99%

“…When the operation point of the converter changes, the quantitativebased PI controller can also achieve satisfactory DC-link voltage control performance. In addition, the battery equalizing charge/discharge control architecture mentioned in Reference [17] is used in this paper. However, the parameters of the charge/discharge PI controller mentioned in Reference [17] are acquired through the "trial and error" method; therefore, a longer amount of time will be required in order to obtain appropriate controller parameters.…”

Section: Maximum Power Pointmentioning

confidence: 99%

“…Furthermore, whereas the controller designed using the Bode plot can obtain the controller parameters quickly but does not take the converter's dynamic characteristic of wide operating spectrum into consideration, and thus is only able to obtain the dynamic response under certain conditions; once the operating point changes, the system will be unable to operate under the better performance response [9,10]. For other existing intelligent controllers such as the particle swarm optimization (PSO) [11,12], genetic algorithm (GA) [13,14], sliding mode control [15,16], fuzzy control [17][18][19], and neural network [20], although these above controllers can all incorporate the traditional P-I controller into the design, the calculation process for these intelligent algorithms are complex, leading to difficulty in obtaining the design parameters, and is also more difficult to implement in actual application.…”

Section: Introductionmentioning

confidence: 99%

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Quantitative Design for the Battery Equalizing Charge/Discharge Controller of the Photovoltaic Energy Storage System

Chao

Huang

2022

Batteries

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The purpose of this paper is to develop a photovoltaic module array with an energy storage system that has equalizing charge/discharge controls for regulating the power supply to the grid. Firstly, the boost converter is used in conjunction with maximum power point tracking (MPPT) such that the photovoltaic module array (PVMA) can output maximum power at any time. The battery equalizing charge/discharge architecture is composed of multiple sets of bidirectional buck–boost soft-switching converters in serial connection in order to achieve zero-voltage switching (ZVS) and zero-current switching (ZCS) so that when the charge/discharge power is above 150 W, the converter efficiency can be increased by 3%. The voltage and current signals from the battery are captured and input into the digital signal processor (DSP) to establish an equalizing charge/discharge control rule. For the output voltage control of the bidirectional buck–boost soft-switching converter, the dynamic mode is derived by first using the step response at chosen operating point, then quantitatively designing the controller parameters for the converter, so that the output voltage response can meet the pre-defined performance specifications. Finally, actual test results prove that the equalizing charge/discharge time of the quantitative design controller is shortened by more than 10% when compared to the traditional proportional-integral (P-I) controller regardless of charging or discharging; this also proves that the design of the photovoltaic module array with an energy storage system (ESS) that has equalizing charge/discharge controls is valid.

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Research on Buck Converter with Improved Approach Rate Compound Sliding Mode Control Based on PSO

Ning,

Li,

Cao

2024

2024 9th Asia Conference on Power and Electrical Engineering (ACPEE)

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Fuzzy Adaptive Time-Delay Feedback Controlling Chaos in Buck Converter

Cited by 4 publications

References 15 publications

Data encryption based on 7D complex chaotic system with cubic memristor for smart grid

Data encryption based on 7D complex chaotic system with cubic memristor for smart grid

Quantitative Design for the Battery Equalizing Charge/Discharge Controller of the Photovoltaic Energy Storage System

Research on Buck Converter with Improved Approach Rate Compound Sliding Mode Control Based on PSO

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