Tadjine Mohamed

Papers

Total Citations

H-Index

About

Tadjine Mohamed is a leading researcher in intelligent control systems, specializing in the integration of neural networks, fuzzy logic, and sliding mode control for complex, uncertain dynamical systems. His most-cited work, "Decentralized RBFNN Type-2 Fuzzy Sliding Mode Controller for Robot Manipulator Driven by Artificial Muscles" (2012, 12 citations), pioneers a robust control architecture that combines Radial Basis Function Neural Networks with Type-2 fuzzy logic to handle system uncertainties in bio-inspired robotics. This contribution has been influential in advancing adaptive control for soft actuators. In a significant interdisciplinary shift, Mohamed also addresses precision alignment challenges in optical wireless communication. His 2020 paper on "Extended Kalman Filter Based Linear Quadratic Regulator Control for Optical Wireless Communication Alignment" (11 citations) introduces a high-precision control strategy for laser beam positioning between underwater mobile robots, effectively mitigating noise effects. This work demonstrates his versatility in applying advanced estimation and control theory to real-world mechatronic systems. With a growing citation record, Mohamed’s research bridges theoretical control innovations and practical implementations, making him a notable figure in both intelligent robotics and optical communication alignment.