Performance Comparison of Various Controllers for DC-DC Synchronous Buck Converter

Lindiya, S. Augusti; Palani, S.; Iyyappan,

doi:10.1016/j.proeng.2012.06.315

Cited by 22 publications

(14 citation statements)

References 11 publications

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“…A FLC is capable of adapting fluctuating operating points, so it is utilized as non-linear controller for DC-DC converters [14,21,22]. To obtain stable operation of buck and boost converter, classical PI and FLC based control strategy is presented in [18,23,24]. To rectify the problem of nonlinear nature of DC-DC converter, a FLC is used as it does not require precise mathematical model of plant.…”

Section: Issn: 2321-9653; Ic Value: 4598; Sj Impact Factor: 6887 Vomentioning

confidence: 99%

Design and Assessment of Digital PID and Fuzzy Controller for DC-DC Converter

Sharma¹

2018

IJRASET

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Section: Issn: 2321-9653; Ic Value: 4598; Sj Impact Factor: 6887 Vomentioning

confidence: 99%

Design and Assessment of Digital PID and Fuzzy Controller for DC-DC Converter

Sharma¹

2018

IJRASET

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“…The wind turbine system is based on the integration of the "Wind Turbine" model and the DC machine, as shown in Figure 3. The buck converter model in Figure 4 consists of a switching device (normally MOSFET [32,34,35]), an inductor, a capacitor, a diode, a resistor (load), and a feedback element. A voltage mode-controlled feedback buck converter [32,36] is derived by comparing the voltage output with a reference value.…”

Section: Matlab/simulink Modelmentioning

confidence: 99%

A conceptual implementation of a buck converter for an off-grid hybrid system consisting of solar and wind turbine sources

Rahman¹,

Razak²,

Hassan³

2016

Turk J Elec Eng & Comp Sci

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Abstract:A hybrid renewable power generation system is proposed through parallel connection between two potential energy resources: photovoltaic (PV) and wind turbines. The method consists of incorporating a buck converter connected by a wind turbine to provide adjustment according to PV potential. Unlike the conventional buck-boost converter topology that is normally used, this research tries to emphasize the use of a buck converter as part of the system configuration. Design schemes were carefully performed and the postdesign system was tested through system simulation with MATLAB/Simulink software. The simulated system offers promising and significant results, thus making it suitable for hardware implementation.

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“…Their low cost, small size, and large output‐power delivering capability make them ideal for consumer electronics, power supplies for personal computers, adjustable DC motor speed drives, and renewable energy conversion systems etc . A plethora of feedback control schemes have been proposed by research engineers to optimally control the output voltage of buck converters, even in the presence of load transients and input‐voltage fluctuations . The proportional‐integral‐derivative (PID) controllers have been widely used to effectively regulate the output voltage of DC‐DC converters due to their simple structure .…”

Section: Introductionmentioning

confidence: 99%

“…2 A plethora of feedback control schemes have been proposed by research engineers to optimally control the output voltage of buck converters, even in the presence of load transients and input-voltage fluctuations. [3][4][5] The proportional-integral-derivative (PID) controllers have been widely used to effectively regulate the output voltage of DC-DC converters due to their simple structure. 6,7 It is a linear model-free controller that provides a robust control effort based on the weighted sum of the error dynamics.…”

Section: Introductionmentioning

confidence: 99%

Time‐optimal control of DC‐DC buck converter using single‐input fuzzy augmented fractional‐order PI controller

Saleem

Shami

Mahmood-ul-Hasan

2019

Int Trans Electr Energ Syst

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Summary This paper presents a robust and optimal output‐voltage tracking controller for a DC‐DC buck converter. A fractional‐order proportional‐integral (FPI) controller is primarily used to eliminate the steady‐state error and damp the oscillations. In order to improve the error convergence rate of the response, the FPI controller is augmented with a single‐input fuzzy‐logic based precompensator stage. The fuzzy precompensator aggregates the information regarding the error and error derivative using the signed‐distance method. The derived aggregated signal is used to infer logical control decisions based on a predefined one‐dimensional rule base. The simplification yields shorter computation time and a piecewise linear control surface that improves the system's immunity against exogenous disturbances and unprecedented nonlinearities. The error derivative is indirectly computed by measuring the capacitor current in real time. This modification further enhances the computational efficiency, offers minimum‐time transient recovery, and compensates the hysteresis effect rendered by parasitic impedances. The controller gains are optimally selected using the particle swarm optimization algorithm. Credible hardware‐in‐the‐loop experiments are conducted to validate the time optimality and robustness of the proposed controller. The experimental results clearly demonstrate the significant improvement rendered by the proposed controller in the system's reference tracking performance, disturbance‐rejection capability, and transient recovery time.

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Performance Comparison of Various Controllers for DC-DC Synchronous Buck Converter

Cited by 22 publications

References 11 publications

Design and Assessment of Digital PID and Fuzzy Controller for DC-DC Converter

Design and Assessment of Digital PID and Fuzzy Controller for DC-DC Converter

A conceptual implementation of a buck converter for an off-grid hybrid system consisting of solar and wind turbine sources

Time‐optimal control of DC‐DC buck converter using single‐input fuzzy augmented fractional‐order PI controller

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