Papers
3
Total Citations
33
H-Index
2
About
Belem Saldivar’s research lies at the intersection of advanced control theory, robotics, and bioinspired systems, with a focus on fault-tolerant mechanisms and rehabilitation technology. Her most cited work, “An SVM-Based Neural Adaptive Variable Structure Observer for Fault Diagnosis and Fault-Tolerant Control of a Robot Manipulator” (2020, 29 citations), addresses critical challenges in ensuring the reliability of multi-degree-of-freedom robotic systems used in medical and automotive applications. By integrating support vector machines with neural adaptive observers, she developed a robust framework for detecting and compensating for faults under uncertain, nonlinear operating conditions—a contribution that enhances safety and performance in complex manipulators. Saldivar also explores novel robotic morphologies, as seen in her work on a nonlinear oscillator-based gait generation for an aero-terrestrial bioinspired system (2020), drawing inspiration from Hymenoptera insects to coordinate 12 terrestrial degrees-of-freedom. More recently, her research on tracking and stiffness control via sliding modes for a wrist-elbow rehabilitator (2024) demonstrates a commitment to practical, human-centered robotics. With a growing citation impact, Saldivar’s work is shaping resilient control strategies for next-generation robotic systems.
Research Focus
Key Achievements
Top Papers
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