Mohammad Mahdi Fateh
Papers
2
Total Citations
4
H-Index
2
About
Mohammad Mahdi Fateh is a researcher specializing in the robust and intelligent control of robotic systems, with a particular focus on mobile robots and mobile manipulators operating under uncertainty. His work addresses the critical challenge of achieving precise motion control for low-cost platforms, which are often plagued by modeling inaccuracies and external disturbances. A key contribution is his development of a robust control design that employs a radial basis function neural network (RBFNN) as an uncertainty compensator, enabling a low-cost mobile robot to maintain stable performance despite significant system unknowns. This work, cited 2 times, demonstrates a practical approach to bridging the gap between theoretical control and real-world hardware limitations. Further expanding on intelligent control strategies, Fateh has also designed a fuzzy logic-based motion controller for nonholonomic wheeled mobile manipulator robots. This approach, also cited 2 times, allows for adaptive trajectory tracking in the presence of uncertainties without requiring an exact system model. Collectively, his research provides valuable, implementable frameworks for enhancing the autonomy and reliability of cost-effective robotic platforms, a crucial step for their deployment in real-world applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2