Optimizing weighted voltage mode control for enhanced output cross-regulation in multi-output DC/DC converters

Abstract

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.