Improved dynamic response of isolated full bridge DC to DC converter using BATA optimization tuned fuzzy sliding mode controller for solar applications

Anand, R.; Samuel, T. S. Arun; Mary, P. Melba

doi:10.1016/j.ijhydene.2017.07.109

Cited by 7 publications

(6 citation statements)

References 24 publications

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“…Obviously, the inequality (36) with a given w 1 > 0 and any w 2 > 0 holds, if the inequality (36) with a given w 1 > 0 and w 2 = 0 holds. Hence, when the inequalities (11) APPENDIX E: PROOF OF THEOREM 3…”

Section: Appendix C: Proof Of Corollarymentioning

confidence: 99%

“…Although these conventional control approaches may be adequate in some cases, the controller performance is quite limited, and the design involves a number of heuristic procedures, which lack theoretical guarantees. This motivates the study of advanced control technology for DC-DC converters, and a large number of control methods have been developed or tailored to control problems of DC-DC converters, e.g., sliding mode control [9], [10], fuzzy logic control [11], adaptive control [12], robust control [13] model predictive control [14], [15], artificial neural network control [16], Lyapunov-based control [17], [18], to just mention a few.…”

Section: Introductionmentioning

confidence: 99%

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Sampled-Data Control With Adjustable Switching Frequency for DC–DC Converters

Yan

Shu

Sharkh

et al. 2019

IEEE Trans. Ind. Electron.

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In this paper, a novel sampled-data control approach is proposed for DC-DC converters. The DC-DC power electronic converter is modeled as a sampled-data switched affine system according to the status of the power switch. A novel switching control algorithm is synthesized by using the switched Lyapunov theory. The proposed approach is able to not only drive the output to a prescribed set point from any initial condition but also track a varying reference signal, and the switching frequency can be adjusted online with guaranteed stability. In addition, with this approach, CCM and DCM operations can be treated in a unified way. The effectiveness and merits of the proposed method are illustrated by experiments on a laboratory prototype.

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Section: Appendix C: Proof Of Corollarymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sampled-Data Control With Adjustable Switching Frequency for DC–DC Converters

Yan

Shu

Sharkh

et al. 2019

IEEE Trans. Ind. Electron.

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“…[17] proposed an BFBIC which features wide input range and resilient operation along 0 to 100 percent of load current change with a set of active voltage clamping snubber and active start-up circuits, avoid the start-up problem caused by the low output capacitor voltage at the beginning of start-up, the leakage inductance of the isolation transformer. To achieve the purpose of regulating control of the output voltage under varying load, the literature [18] deals with the achievement of the dynamic response of high gain DC-DC converter in PV system using BAT Algorithm optimization tuned fuzzy sliding mode controller. The dynamic and transient response of the isolated full bridge DC-DC converter are improved under starting and load step change conditions.…”

Section: Introductionmentioning

confidence: 99%

An Improved Gray Wolf Optimizer MPPT Algorithm for PV System With BFBIC Converter Under Partial Shading

et al. 2020

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Based on the boost full bridge isolated converter (BFBIC) topology and considering the sudden changes in the external environment, a global maximum power point tracking (GMPPT) control strategy based on an improved gray wolf optimizer (IGWO) algorithm is proposed in this paper. In the strategy, a nonlinear tangent trigonometric function as a convergence factor is integrated into the gray wolf optimizer (GWO) algorithm. In addition, the active-clamp circuit and phase-shift are used to implement the soft switch technology for BFBIC converter in photovoltage (PV) system. Finally, the maximum power point tracking (MPPT) performance on PV system with the proposed IGWO algorithm under static and dynamic partial shading conditions (PSCs) was investigated and compared with other common perturb and observe(P&O), particle swarm optimization (PSO), artificial bee colony (ABC), adapt inertia weight salp swarm algorithm (WSSA), salp swarm algorithm with grey wolf optimizer (SSA-GWO), SSA with PSO (SSA-PSO), enhanced GWO (EGWO) MPPT algorithms. The effectiveness and stability of the proposed control strategy are validated, especially tracking speed under PSCs. Simulation results show that the BFBIC topology with the proposed IGWO algorithm outperforms other algorithms on most cases, especially only takes the tracking time of 0.24s and reaches the efficiency of 98.54% under the most severe PSCs. INDEX TERMS Boost full bridge isolated converter (BFBIC), improved grey wolf optimizer (IGWO), global maximum power point tracking (GMPPT), partial shading conditions (PSCs)

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“…Without the wind turbines, the efficacy of this hybrid BA is used in comparison with other algorithms. In the study by Anand et al (2017), bat tuned fuzzy sliding mode-controlled separate DC to DC converter was suggested for resolving the problem of OPF. The proposed topology eliminated overshoot and ripples.…”

Section: Introductionmentioning

confidence: 99%

A hybrid bat–dragonfly algorithm for optimizing power flow control in a grid-connected wind–solar system

Gonal

Sheshadri

2019

Wind Engineering

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For the fulfillment of global energy demand, the best options are renewable energy sources due to their ease of availability and non-polluting nature. Hybrid system improves the efficiency of the overall system and provides better balance in energy supply. This study proposes a hybrid bat–dragonfly algorithm for providing optimal power flow in the wind–solar system by tuning the controller parameters. Bat algorithm has the featureless computing time with low accuracy, and dragonfly algorithm has the feature of high accuracy with more computing time. The accuracy of the controller tuning gets improved with less computational time by integrating the operations of both bat and dragonfly algorithms. Fuzzy rationale–based maximum power point tracking extracts the maximum power available in wind–solar system. The results show that the proposed hybrid algorithm provides better execution in the tuning of controller parameters compared with the existing optimization methods with a low level of total harmonic distortion. Furthermore, the proposed hybrid bat–dragonfly algorithm outperforms the benchmark optimization algorithms when tested.

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Improved dynamic response of isolated full bridge DC to DC converter using BATA optimization tuned fuzzy sliding mode controller for solar applications

Cited by 7 publications

References 24 publications

Sampled-Data Control With Adjustable Switching Frequency for DC–DC Converters

Sampled-Data Control With Adjustable Switching Frequency for DC–DC Converters

An Improved Gray Wolf Optimizer MPPT Algorithm for PV System With BFBIC Converter Under Partial Shading

A hybrid bat–dragonfly algorithm for optimizing power flow control in a grid-connected wind–solar system

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