Afshar Shamsi Jokandan

Papers

Total Citations

H-Index

About

Afshar Shamsi Jokandan is a researcher specializing in intelligent control systems for robotic manipulators, with a particular focus on neuro-fuzzy and adaptive control methodologies. His work addresses the critical challenge of achieving precise position control and fault tolerance in complex robotic systems, which are essential for flexible automation and human-robot collaboration. Jokandan’s most cited paper, “A new method for position control of a 2-DOF robot arm using neuro–fuzzy controller” (2012, 19 citations), introduces an innovative hybrid control approach that combines neural networks and fuzzy logic to enhance the accuracy and reliability of robot arm movements. This contribution is foundational for developing more robust and autonomous robotic systems capable of detecting and isolating faults during operation. In his subsequent work, “Performance Comparison of Type-1 and Type-2 Neuro-Fuzzy Controllers for a Flexible Joint Manipulator” (2019, 2 citations), Jokandan extends his research to compare advanced control strategies, offering insights into the trade-offs between model complexity and control performance. His research is particularly relevant for students and engineers working on intelligent automation, providing practical frameworks for designing controllers that improve the safety and efficiency of robots in dynamic environments.