The widespread adoption of electric vehicles requires advanced charging control strategies capable of achieving accurate current regulation and improved transient performance. This paper presents a recurrent neural network–Integrated adaptive sliding mode controller (RNN-ASMC) for the control of a DC–DC buck converter...
Somendra Banerjee, Awadhesh Kumar, V. K. Giri· Engineering Research Express· 0 citations
This research paper compares a conventional proportional-integral (PI) controller with a fuzzy-based sliding mode controller (FSMC) for speed control of a brushless DC (BLDC) motor powered by a Landsman DC-DC converter for electric vehicle (EV) applications. MATLAB/Simulink is used to model and simulate the proposed sy...
S. Sahana, K. Sasikala· International Journal of Pow...· 0 citations
The increasing integration of renewable energy resources into modern power systems has created significant challenges in maintaining voltage stability, frequency regulation, and overall microgrid reliability due to the intermittent nature of solar and wind generation. This study proposes an Adaptive Sliding Mode Contro...
Abigail Chidimma Odigbo, O. K. Obi, C. C. Nwobu et al.· Natura: Journal of Multidisc...· 0 citations
Experimental results demonstrate that the proposed method outperforms traditional PID, fuzzy PID, and sliding mode control approaches by achieving superior speed tracking, enhanced disturbance rejection, greater parameter robustness, reduced overshoot, faster settling time, and lower steady-state error.
Zhi-Sheng Cai, Tong-Yu Zhan· International Journal of Dyn...· 0 citations
This paper presents a robust discrete-time sliding mode controller (DT–SMC) for a bidirectional DC/DC converter that is used as an energy storage interface in DC microgrids. The proposed controller is implemented in a hierarchical cascaded control structure comprising an inner current loop and an outer voltage loop, to...
L. Ahmethodžić, S. Huseinbegović· IEEE Open Journal of Power E...· 0 citations
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