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In this study, we investigate the performance of a boost converter regulating its output voltage using two control methods: Proportional-Integral (PI) control and neural control. Both methods are implemented on a simulation platform (Matlab/Simulink) and evaluated in terms of accuracy, response speed, and robustness to disturbances. Indeed, the output voltage of converters exhibits imperfections that require a control method to optimize efficiency when applying a variable load. Results show that neural control offers superior performance in terms of accuracy and response time, with faster and more precise regulation of the output voltage. On the other hand, PI control proves to be more robust against disturbances. These findings can help guide the selection of the appropriate control method for a boost converter based on the specific requirements of each application.

This article proposes a method of management and control of a continuous bus powered by renewable energies for autonomous applications. The DC bus is obtained from two systems of renewable sources (the solar system and the wind system) and storage battery (Lithium Ion). The continuous bus control and management procedure require efficiency in the control of the charge and discharge of the battery according to the load energy demand (DC Motor). The battery charging process is non-linear, varying over time with considerable delay, so it is difficult to achieve the best performance on control with energy management using traditional control approaches. A fuzzy control strategy is used in this article for battery control. To improve battery life, fuzzy control manages the desired state of charge (SOC). The entire system designed is modeled and simulated on MATLAB/Simulink Environment.