Farah Bouakrif
Papers
10
Total Citations
254
H-Index
8
About
Farah Bouakrif is a distinguished control systems researcher whose work has profoundly shaped the field of intelligent control for robot manipulators, with a particular focus on iterative learning control (ILC) and trajectory tracking. Over more than a decade of sustained contributions, she has tackled some of the most challenging problems in robotic control, including systems subject to external disturbances, unknown model parameters, and restricted sensor availability. Her landmark 2011 paper on velocity observer-based ILC, which has garnered 64 citations, introduced an elegant framework for achieving precise trajectory tracking without relying on velocity measurements — a significant practical advancement for real-world robotic systems. Bouakrif has progressively extended this foundational work through high-order ILC schemes validated via Lyapunov theory, adaptive radial basis function approaches capable of handling unknown dead-zone inputs, and forgetting factor strategies for robots with entirely unknown models. Her 2016 and 2018 contributions, each accumulating 34 citations, further demonstrate the breadth and depth of her influence. With a cumulative body of work exceeding 250 citations, Bouakrif stands as an important voice in modern robotics control theory, bridging rigorous mathematical analysis with practical engineering applications.
Research Focus
Key Achievements
Top Papers
- 1Velocity observer-based iterative learning control for robot manipulators64 citations · 2011
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- 8PASSIVITY-BASED CONTROLLER– OBSERVER FOR ROBOT MANIPULATORS12 citations · 2010
- 9Passivity-based controller-observer for robot manipulators8 citations · 2008
- 10Iterative learning control for robot manipulators6 citations · 2007