Papers
17
Total Citations
152
H-Index
7
About
Fabian Andres Lara-Molina is a robotics and control engineer whose research sits at the intersection of parallel robot design, robust control theory, and reliability analysis under uncertainty. His work has made meaningful contributions to the optimal design of parallel manipulators, particularly planar and flexible-joint systems, where he has developed multi-objective frameworks balancing workspace size, dynamic dexterity, and control energy — research that has garnered over 24 citations. Lara-Molina has also advanced robust control methodologies, applying H∞ techniques and Linear Matrix Inequalities to manipulator control under parametric uncertainty, as well as pioneering generalized predictive control strategies experimentally validated on platforms such as the Orthoglide robot. A distinctive thread in his work is the rigorous treatment of uncertainty: he has employed stochastic approaches for 6-DOF parallel robots and developed a novel fuzzy-theory-based framework for kinematic reliability assessment, cited over 21 times, enabling probabilistic quantification of positioning errors. With a body of work spanning optimal design, predictive and fuzzy control, and reliability-centered performance criteria, Lara-Molina has established himself as a versatile contributor to modern robotics research, offering practical tools for engineers designing high-performance robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Multi-objective optimal design of flexible-joint parallel robot24 citations · 2018
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- 3Robust H∞ Computed torque Control for Manipulators17 citations · 2018
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- 5Robust generalized predictive control of the Orthoglide robot11 citations · 2014
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- 10Application of predictive control techniques within parallel robot6 citations · 2012