Mohamed El Hossine Daachi
University Mohamed El Bachir El Ibrahimi of Bordj Bou Arreridj
Papers
3
Total Citations
17
H-Index
3
About
Mohamed El Hossine Daachi is a robotics and control systems researcher whose work bridges adaptive control, artificial intelligence, and real-world applications. His primary research areas include nonlinear control, sliding mode control, and reinforcement learning for autonomous systems. Daachi’s most impactful contribution is a 2024 paper on a real-time adaptive super twisting algorithm optimized by particle swarm optimization (PSO), applied to exoskeleton robots—a work that has already garnered 10 citations for its novel approach to handling dynamic uncertainties in trajectory tracking. He also pioneered the integration of Q-learning on Arduino platforms for autonomous mobile robot navigation in COVID-19 field hospitals (2021, 4 citations), demonstrating how reinforcement learning can be deployed on low-cost hardware for disinfection and logistics tasks during the pandemic. Earlier, his 2004 work on neural networks for redundant robot manipulators with obstacle avoidance (3 citations) laid groundwork for constrained motion control. Daachi’s research is notable for its practical orientation—moving from theoretical neural network control to adaptive algorithms and embedded AI solutions that address pressing societal needs. His work exemplifies how advanced control theory can be translated into deployable robotic systems.
Research Focus
Key Achievements
Top Papers
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