Mohamed Jasim
Papers
1
Total Citations
3
H-Index
1
About
Mohamed Jasim is a rising researcher in advanced robotics and intelligent control systems, with a focus on enhancing the precision and stability of robot manipulators under real-world uncertainties. His most-cited work, "Bat optimization of hybrid neural network-FOPID controllers for robust robot manipulator control," tackles critical challenges in position and trajectory tracking—specifically poor accuracy and unstable performance caused by unidentified loads and external disturbances. Jasim proposes three innovative control structures that synergize bat-inspired metaheuristic optimization with hybrid neural network and fractional-order PID (FOPID) controllers, achieving robust, adaptive responses for multi-input, multi-output robotic systems. Though early in his career, his contributions are gaining traction, with this paper already accumulating 3 citations since its 2025 publication, signaling growing interest from the robotics and control engineering communities. Jasim’s work stands out for its practical integration of bio-inspired algorithms and neural networks, offering a scalable pathway toward more resilient autonomous systems. As he continues to refine these hybrid approaches, his research promises to influence next-generation industrial and service robotics, where reliability under unpredictable conditions is paramount.
Research Focus
Key Achievements
Top Papers
- 1