Amineh Yazdizadeh Baghini
Papers
1
Total Citations
3
H-Index
1
About
Amineh Yazdizadeh Baghini is a researcher focused on advanced control systems and robotics, with a particular emphasis on under-actuated mechanical systems. Her key research areas include optimal fuzzy control, metaheuristic optimization algorithms, and the stabilization of complex robotic manipulators. Her most notable contribution is the design of an optimal fuzzy controller for a two-link planar horizontal under-actuated manipulator, where she applied the Teaching-Learning-Based Optimization (TLBO) algorithm to fine-tune controller parameters for enhanced stabilization performance. This work, published in 2019, has garnered 3 citations, reflecting its relevance in the niche field of under-actuated robotics. Baghini’s research bridges the gap between intelligent control theory and practical robotic applications, offering innovative solutions for systems with fewer actuators than degrees of freedom. Her approach demonstrates how bio-inspired optimization can improve the efficiency and robustness of fuzzy logic controllers, making her work a valuable reference for students and researchers exploring advanced control strategies in robotics and automation.
Research Focus
Key Achievements
Top Papers
- 1