Felizardo Cuevas

Instituto Tecnológico de Tijuana

Papers

10

Total Citations

171

H-Index

8

About

Felizardo Cuevas is a researcher specializing in intelligent control systems, with a particular focus on type-2 fuzzy logic, metaheuristic optimization, and autonomous mobile robotics. His work centers on developing sophisticated control strategies that enable mobile robots to navigate complex environments with precision, adaptability, and real-time responsiveness. Cuevas has made significant contributions to the field by advancing the application of both interval and generalized type-2 fuzzy systems in robot control, particularly for omnidirectional mobile platforms. A hallmark of his research is the integration of nature-inspired metaheuristic algorithms — such as the Shark Smell and Marine Predator algorithms — to optimally tune fuzzy controller parameters, a technically demanding challenge that directly impacts robotic performance. His most cited work (2021, 50 citations) demonstrates how these bio-inspired optimization techniques can yield superior membership function configurations for fuzzy tracking controllers. With a consistent publication record spanning 2018 to 2022 and accumulating over 170 citations, Cuevas has established himself as a productive voice in computational intelligence applied to robotics. His research is particularly valuable for students and engineers seeking robust, adaptive control frameworks for autonomous systems operating in dynamic, real-world environments.

Research Focus

Key Achievements

8
H-Index
10
Papers
171
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Optimal Setting of Membership Functions for Interval Type-2 Fuzzy Tracking Controllers Using a Shark Smell Metaheuristic Algorithm
50 citations · 2021
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Instituto Tecnológico de Tijuana

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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