Mozhdeh Adibi
Papers
1
Total Citations
56
H-Index
1
About
Mozhdeh Adibi is a leading researcher in advanced control systems, specializing in nonlinear and adaptive control strategies for robotic manipulators. Her work addresses critical challenges in handling system uncertainties, particularly through the innovative integration of sliding mode control (SMC) with fuzzy logic and optimization algorithms. Her most-cited paper, "Model-Free Adaptive Fuzzy Sliding Mode Controller Optimized by Particle Swarm for Robot Manipulator" (2013, 56 citations), introduces a novel framework that combines the robustness of SMC with the adaptability of fuzzy logic, fine-tuned via particle swarm optimization. This approach eliminates the need for precise system models, making it highly effective for real-world robotic applications where uncertainties are inevitable. Adibi’s contributions have significantly advanced the field of intelligent control, offering practical solutions for improving robot precision and stability. Her work is widely recognized for bridging theoretical control methods with applied robotics, inspiring further research in adaptive and model-free control systems.
Research Focus
Key Achievements
Top Papers
- 1