Neamah, O.N.Abumelh, A.S.Bayir, R.2024-09-292024-09-292024979-835039452-8https://doi.org/10.1109/ACDSA59508.2024.10467663https://hdl.handle.net/20.500.14619/9483Aksaray University; IEEE; University of Seychelles2024 International Conference on Artificial Intelligence, Computer, Data Sciences, and Applications, ACDSA 2024 -- 1 February 2024 through 2 February 2024 -- Victoria -- 198277This study introduces an innovative approach leveraging Newton-Raphson optimization to enhance the control of Model Predictive Control (MPC) in DC-DC Boosters, a technology extensively employed in electric vehicles, renewable energy systems, microgrids, and diverse applications. In addressing inherent challenges such as pronounced overshoot and oscillations observed in traditional MPC and other controllers like Hysteresis Controller (HC) and Proportional-Integral (PI), the proposed method demonstrates remarkable efficiency. The application of Newton-Raphson optimization yields significant improvements in the performance of the DC-DC Booster, presenting a promising avenue for optimizing control strategies in these crucial systems. This advancement holds great potential to substantially contribute to the stability and effectiveness of DC-DC Boosters across various operational scenarios, thereby making notable strides in the field of control systems for critical applications. © 2024 IEEE.eninfo:eu-repo/semantics/closedAccessDC-DC BoosterHysteresis ControllerModel Predictive Control (MPC)Newton-RaphsonProportional-Integral (PI)Conference Object10.1109/ACDSA59508.2024.104676632-s2.0-85189934166N/A