Jihad Younis
Papers
1
Total Citations
1
H-Index
1
About
Jihad Younis is a rising scholar in intelligent control systems and autonomous robotics, with a focus on advancing adaptive control strategies for complex, multi-input multi-output (MIMO) platforms. His most cited work introduces a novel intelligent neuro-fuzzy adaptive control framework for self-balancing two-wheeled autonomous robots, leveraging recursive resolution of the matrix Diophantine equation. This method uniquely integrates maximum likelihood identification with an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based predictive control scheme, enabling real-time adaptation and robust performance in dynamic environments. Though early in his career—with his top paper accumulating 1 citation as of 2025—Younis’s contribution stands out for its theoretical depth and practical relevance, addressing a longstanding challenge in MIMO system control. His work bridges fuzzy logic, neural networks, and predictive control, offering a scalable solution for autonomous vehicles and robotic platforms. As an emerging researcher, Younis demonstrates strong potential to influence future developments in intelligent control, particularly in applications requiring high precision and adaptability. His innovative approach marks him as a promising voice in the field of autonomous systems and control engineering.
Research Focus
Key Achievements
Top Papers
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