Yacine Amirat

Université Paris-Est Créteil, Paris-Est Sup, Polytechnic School of Algiers

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About

Yacine Amirat is a robotics and intelligent systems researcher whose work spans advanced robot control, neural network-based learning, and assistive technologies. He is perhaps best known for his pioneering contributions to the control of parallel robots, particularly the C5 parallel robot — a complex 6-degree-of-freedom system that presents significant modeling and control challenges. His most influential work, "A robust adaptive control of a parallel robot" (2010, 31 citations), introduced an innovative approach coupling sliding mode control with multi-layer perceptron neural networks, elegantly bypassing the need for inverse dynamic models — a notable achievement in reducing computational complexity. Building on this foundation, Amirat extended his methods to adaptive force/position control for constrained robotic motions, further demonstrating the versatility of neural network-driven approaches. His editorial leadership of a special issue on Assistive and Rehabilitation Robotics (2017) highlights his commitment to socially impactful applications, bridging fundamental control theory with real-world human needs. More recently, his interest has broadened to context-aware pervasive computing, addressing uncertainty in sensor-rich environments. Collectively, Amirat's contributions reflect a research vision that unifies rigorous control theory, machine learning, and human-centered robotics.