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Weighted voltage mode control is a widely used method for regulating multiple output DC-DC converters, but inconsistent outcomes are often observed in design due to the complexity of the weighting variable optimization. This study proposes an optimization-based approach to accurately estimate the optimal weighting factors for improved output voltage regulation in multiple output forward DC-DC converters. Three optimization algorithms, the Imperialist Competitive Algorithm (ICA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO) are compared for their speed and accuracy in estimating the weighting factors. Additionally, a Fuzzy Logic Controller (FLC) is used to further reduce the overall steady-state error and improve transient characteristics. Simulations are performed using the MATLAB/Simulink software, and the results show that the proposed strategy significantly enhances output cross-regulation in multiple output forward DC-DC converters. The ICA-based weighting factor estimator is found to be the most effective algorithm among the three optimization algorithms tested. The main contribution of this study is to provide a more efficient and accurate method for estimating the weighting factors in multiple output forward DC-DC converters, which can lead to improved performance and reliability in various applications.


Multiple outputs forward DC-DC converters Imperialist competitive algorithm Particle swarm optimization Ant colony optimization Weighting factor method

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Safarishaal, M., & Sarvi, M. (2023). Optimizing weighted voltage mode control for enhanced output cross-regulation in multi-output DC/DC converters. Future Technology, 3(1), 32–39. Retrieved from
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