Investigation of a Voltage-Mode Controller for a dc-dc Multilevel Boost Converter

Jiang, Wentao; Chincholkar, Satyajit Hemant; Chan, Chok-You

doi:10.1109/tcsii.2017.2723660

Cited by 41 publications

(26 citation statements)

References 20 publications

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“…According to Table 5, the lowest best fits is from (2,1,1) with 19.96%, while the highest best fits is (4,1,1) with 92.25% in value. 19.96% 3,1,143.41% (4,1,1) 63.43% (2,2,1) 75.22% (4,2,1) 92.25% Figure 6. Measured and simulated OE model structure The discrete time polynomial equation for OE model structure is shown in (11).…”

Section: Resultsmentioning

confidence: 99%

“…The input and output data from the two-level boost converter had been compared, and the best result from the ARX model structure yielded 96.81% best fits. The discrete time polynomial for ARX model structure for system identification in MATLAB/Simulink software can be expressed as (4). The best mathematical models for ARX model structure (5,4,1) are expressed as (5) and (6).…”

Section: Model Developmentmentioning

confidence: 99%

“…The discrete time polynomial for ARX model structure for system identification in MATLAB/Simulink software can be expressed as (4). The best mathematical models for ARX model structure (5,4,1) are expressed as (5) and (6). 1,1,1) 1.36% (2,1,1) 41.78% (3,2,1) 76.70% (4,2,1) 94.03% (5,4,1) 96.81% Table 4 shows the comparison for best fits for five random model orders.…”

Section: Model Developmentmentioning

confidence: 99%

“…Boost converter is one of the most popular converters to step up the output voltage. Boost converters are widely used in various applications such as in renewable energy system, electrical and electronic devices, as well as electrical vehicles [2][3][4][5]. Lately, researchers particularly studying control system have gained more interests in voltage regulation issues related to DC/DC boost converter [4].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Simulation and modeling of two-level DC/DC boost converter using ARX, ARMAX, and OE model structures

Amran

Bakar

Jalil

et al. 2020

IJEECS

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<span>This paper presents simulation and modeling of two-level DC/DC boost converter using system identification technique. The main objective is to identify the unknown mathematical model from designated converter that has 2 modes of operation. Signals from the converter were processed based on the impulse response from input and output voltages, which were in time domain data. Auto Regressive with eXogenous (ARX), Auto Regressive Moving Average with eXogenous (ARMAX), and Output-Error (OE) model structure techniques had been employed to generate a model from the converter, whose validation was based on coefficient of determination (R<sup>2</sup>) or best fits criterion. The result shows that the ARX model structure produced the best model with 94.03%, compared to ARMAX and OE with 93.70% and 92.25% respectively. In terms of stability for open-loop analysis, the ARX model structure gave the most stable system.</span>

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Section: Resultsmentioning

confidence: 99%

Section: Model Developmentmentioning

confidence: 99%

Section: Model Developmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Simulation and modeling of two-level DC/DC boost converter using ARX, ARMAX, and OE model structures

Amran

Bakar

Jalil

et al. 2020

IJEECS

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show abstract

“…DC-DC converters are employed in a variety of applications such as industrial controls, audio applications, power adapters and chargers, electric vehicles, electronic appliances, power supplies, renewable systems, aerospace equipment, and many other modern types of equipment that operate on DC [1][2][3]. Flyback converters (FCs) are a frequently used type of DC converter which may operate over a broad range of unregulated DC voltage.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence-Based Controller for DC-DC Flyback Converter

et al. 2019

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This paper presents an intelligent voltage controller designed on the basis of an adaptive neuro-fuzzy inference system (ANFIS) for a flyback converter (FC) working in continuous conduction mode (CCM). The union of fuzzy logic (FL) and adaptive neural networks (ANN) makes ANFIS more robust against model parameters’ uncertainties and perturbations in input voltage or load current. ANFIS inherits the advantages of structured knowledge representation from FL and learning capability from NN. Comparative analysis showed that the ANFIS controller offers not only the superior transient response characteristics, but also excellent steady-state characteristics compared to those of the FL controller (FLC) and proportional–integral–derivative (PID) controllers, thus validating its superiority over these traditional controllers. For this purpose, MATLAB/Simulink environment-based simulation results are presented for validation of the proposed converter compensated system under all operating conditions.

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A transformer‐less single‐switch boost converter with high‐voltage gain and mitigated‐voltage stress applicable for photovoltaic utilizations

Yin

Ghaderi

2020

Int Trans Electr Energ Syst

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Many of the photovoltaic (PV) panels generate the low amounts of the voltages under the limited values of the powers. In order to increase these voltages to be applicable for grid utilization, DC-DC boost converters are used. A novel nonisolated transformer-less switched-capacitor-based DC-DC power boost structure is combined with the quadratic converter in this study. The proposed converter has many advantages such the low-voltage stresses on the power components, higher voltage-gain, and ability to supplying the load under the low amounts of the switching time intervals. These features lead to fewer amounts of the currents for the power components in the topology for the continuous conduction mode which means less dynamic losses and higher efficiency. Another advantage of the proposed converter is including only one power switch that simplifies the controller design for implementation purposes. A comprehensive mathematical analysis is presented and simulation with MATLAB/SIMULINK and implemented hardware test results confirm the theoretical investigations. K E Y W O R D S boost converter, continuous current mode, photovoltaic utilizations, switched-capacitor LIST OF SYMBOLS AND ABBREVIATIONS: CCM, continuous current mode; DT, duty cycle; T, time period; I C2,on , currents of capacitors C 2 for the first operation mode; I C3,on , currents of capacitor C 3 for the first operation mode; I C4,on , currents of capacitor C 4 for the first operation mode; I C5, on , currents of capacitor C 5 for the first operation mode; I C2,off , currents of capacitor C 2 for the second operation mode; I C3,off , currents of capacitor C 3 for the second operation mode; I C4,off , currents of capacitor C 4 for the second operation mode; I C5,off , currents of capacitor C 5 for the second operation mode; ID1,on, currents of diode D 1 for the first operation mode; ID 2 ,on, currents of diode D 2 for the first operation mode; ID 3 ,on, currents of diode D 3 for the first operation mode; ID 4 ,on, currents of diode D 4 for the first operation mode; ID 5 ,on, currents of diode D 5 for the first operation mode; ID 6 , on, currents of diode D 6 for the first operation mode; ID 1 ,off, currents of diode D 1 for the second operation mode; ID 2 ,off, currents of diode D 2 for the second operation mode; ID 3 ,off, currents of diode D 3 for the second operation mode; ID 4 ,off, currents of diode D 4 for the second operation mode; ID 5 , off, currents of diode D 5 for the second operation mode; ID 6 ,off, currents of diode D 6 for the second operation mode; ΔiL1, current ripples of the inductor L 1 ; ΔiL2, current ripples of the inductor L 2 ; ΔiL3, current ripples of the inductor L 3 ; ΔVo, voltage ripples of the capacitor C O ; Fs, switching frequency; ΔVc,cap, the ripple value caused by capacitor charging and discharging; P VFD , power losses by diodes.

show abstract

Investigation of a Voltage-Mode Controller for a dc-dc Multilevel Boost Converter

Cited by 41 publications

References 20 publications

Simulation and modeling of two-level DC/DC boost converter using ARX, ARMAX, and OE model structures

Simulation and modeling of two-level DC/DC boost converter using ARX, ARMAX, and OE model structures

Artificial Intelligence-Based Controller for DC-DC Flyback Converter

A transformer‐less single‐switch boost converter with high‐voltage gain and mitigated‐voltage stress applicable for photovoltaic utilizations

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