2017
DOI: 10.1016/j.epsr.2017.08.004
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GA-based robust LQR controller for interleaved boost DC–DC converter improving fuel cell voltage regulation

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Cited by 51 publications
(19 citation statements)
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“…A non-linear model is constructed to represent the operation for each mode and a unified average state-space model is obtained for the converter. The average model of the interleaved boost DC-DC converter is the same as the traditional boost DC-DC converter except that it contains two current inductors [26]. The dynamics of the IBC converter are represented by [26]:…”
Section: -Developed State Space Model Of the Ibcmentioning
confidence: 99%
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“…A non-linear model is constructed to represent the operation for each mode and a unified average state-space model is obtained for the converter. The average model of the interleaved boost DC-DC converter is the same as the traditional boost DC-DC converter except that it contains two current inductors [26]. The dynamics of the IBC converter are represented by [26]:…”
Section: -Developed State Space Model Of the Ibcmentioning
confidence: 99%
“…With regard to the literature, different kinds of control strategies were employed for interleaved boost DC-DC converters for different applications such as adaptive control [16], robust control [10], nonlinear model predictive control (MPC) [17], state feedback control [18,25], sliding mode fuzzy PID control [19], robust adaptive neural network control [20,21], adaptive sliding mode control [22,23], intelligent control [24], and Optimal Robust Linear Quadratic Regulator (LQR) [26].…”
Section: -Introductionmentioning
confidence: 99%
“…PEM fuel cell is an energy conversion device that uses the catalytic oxidation of hydrogen at an anode with the catalytic reduction of oxygen at a cathode to release energy as electricity and heat with the non‐polluting by‐product of water (Figure ).…”
Section: Pem Fuel Cell Modelingmentioning
confidence: 99%
“…With different weighting matrices Q e and R, various gain matrices can be obtained, which indicates that the controller is non-optimal in a true sense. In recent studies, plenty of methods have been reported to solve this type of optimization problem, such as the adaptive particle swarm optimization method [42] and genetic algorithms [43].…”
Section: Design Of the Guaranteed-cost Preview Repetitive Controllermentioning
confidence: 99%