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Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm.

ABSTRACT: In this investigation, differential evolution (DE) algorithm with the fuzzy inference system (FIS) are combined and the DE algorithm is employed in FIS training process. Considered data in this study were extracted from simulation of a 2D two-phase reactor in which gas was sparged from bottom of reactor, and the injected gas velocities were between 0.05 to 0.11 m/s. After doing a couple of training by making some changes in DE parameters and FIS parameters, the greatest percentage of FIS capacity was achieved. By applying the optimized model, the gas phase velocity in x direction inside the reactor was predicted when the injected gas velocity was 0.08 m/s.

SUBMITTER: Babanezhad M

PROVIDER: S-EPMC7840922 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm.

Babanezhad Meisam M Zabihi Samyar S Behroyan Iman I Nakhjiri Ali Taghvaie AT Marjani Azam A Shirazian Saeed S

Scientific reports 20210127 1

In this investigation, differential evolution (DE) algorithm with the fuzzy inference system (FIS) are combined and the DE algorithm is employed in FIS training process. Considered data in this study were extracted from simulation of a 2D two-phase reactor in which gas was sparged from bottom of reactor, and the injected gas velocities were between 0.05 to 0.11 m/s. After doing a couple of training by making some changes in DE parameters and FIS parameters, the greatest percentage of FIS capacit ...[more]

PMID: 33504889

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Project description:This paper presents a hybrid approach that combines a genetic algorithm (GA)-optimized type-2 fuzzy logic controller (T2FLC) with a fractional-order technique for enhanced control of a microgrid system. The T2FLC approach is employed to handle the inherent uncertainties in the microgrid due to fluctuating renewable energy inputs and varying loads. The GA optimizes the parameters of the designed FO-T2FLC approach, ensuring optimal performance under different operational conditions. This developed strategy is a modification and development of the traditional approach, as it is characterized by rapid dynamic response, high durability, distinctive performance, ease of application, and inexpensive. Also, this designed strategy does not depend on the mathematical model of the studied system, which gives satisfactory results if the system parameters change. The microgrid system on the direct current side features a photovoltaic array with battery storage. In contrast, the alternating current section comprises a multi-functional voltage source inverter integrated with a shunt active power filter. This setup delivers energy to the connected loads and the network. To manage the system effectively; traditional power control methods (direct power control and space vector modulation) are used for the alternating current section. Additionally, the proposed regulator control the direct current bus voltage loop, regulate the reactive and active power loops of the network, and compensate for the total harmonic distortion in the source streams. It also injects the required active power into the network to enhance the competence of the power network. In this work, the efficiency of the proposed FO-T2FLC-GA approach is verified using MATLAB, comparing it to the T2FLC-GA approach and some existing strategies such as third-order sliding mode control. The results obtained highlight the effectiveness and strength of the FO-T2FLC-GA approach in improving power quality and reducing the total harmonic distortion value, as it reduces the total harmonic distortion value of the current by percentages estimated at 80%, 33.87%, and 32.50% in all cases. The FO-T2FLC-GA approach also reduces the steady-state error, undershoot, fluctuations, and overshoot of direct current link voltage compared to the T2FLC-GA approach by percentages estimated at 1.54%, 33.04%, 25%, and 33.04%, respectively. Compared with other works, the proposed approach improves the response time, overshoot, and ripples of direct current link voltage by 59.38%, 50%, and 75%, respectively, compared to the third-order sliding mode control approach. These results could make the designed FO-T2FLC-GA approach a prominent solution in the future in other industrial applications such as propulsion and traction.

Dataset Information

Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm.

Publications

Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm.

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