Mahmoud Moosavi
Papers
2
Total Citations
48
H-Index
2
About
Mahmoud Moosavi is a researcher whose work sits at the intersection of intelligent control systems and biomedical robotics. His primary research areas include nonlinear system control, artificial intelligence (AI)-based controller design, and assistive robotic technologies, particularly for prosthetic applications. Moosavi’s major contributions are twofold. First, he developed a novel AI-based modified PID hybrid fuzzy controller for highly nonlinear systems, a significant advancement in managing the complex dynamics of uncertain mechanical systems. Second, he pioneered a method for estimating ground reaction forces (GRFs) in prosthetic legs using nonlinear Kalman filtering techniques. By integrating a continuous-time extended Kalman filter (EKF) with a robotic system that emulates human hip and thigh motion, his work enables more responsive and natural control of powered transfemoral prostheses. With his most-cited papers accumulating 27 and 21 citations respectively, Moosavi’s research has demonstrably influenced both theoretical control engineering and practical rehabilitation robotics. His achievements highlight a career dedicated to bridging advanced control theory with real-world assistive devices, offering impactful solutions for individuals with limb loss.
Research Focus
Key Achievements
Top Papers
- 1
- 2