Papers
1
Total Citations
4
H-Index
1
About
Ludivina Facundo is a researcher in intelligent control systems, with a focus on neuro-fuzzy networks and adaptive control for nonlinear, discrete-time plants. Her most-cited work, "Adaptive Control with Sliding Mode on a Double Fuzzy Rule Emulated Network Structure" (2018), introduces a novel adaptive controller that integrates sliding mode techniques with dual Fuzzy Rule Emulated Network (FREN) structures. This approach is designed for systems where mathematical models are unknown, demonstrating significant potential for real-world applications in robotics and automation. With 4 citations, this paper highlights her contribution to bridging fuzzy logic and neural networks for robust control. Facundo’s work advances the field of adaptive control by offering a computationally efficient, model-free solution that enhances stability and performance under uncertainty. Her research is particularly valuable for students and engineers exploring intelligent control methodologies, as it provides a practical framework for handling complex, nonlinear dynamics without requiring explicit system models.
Research Focus
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Top Papers
- 1