Sonia Mahjoub
Papers
3
Total Citations
34
H-Index
3
About
Sonia Mahjoub is a control systems researcher whose work focuses on intelligent control strategies for complex mechanical systems, particularly underactuated robots and pneumatic artificial muscle actuators. Her research integrates neural networks, fuzzy logic, and sliding mode control to address fundamental challenges in nonlinear system control, including chattering reduction and uncertainty compensation. Her most cited work, "Radial-basis-functions neural network sliding mode control for underactuated mechanical systems" (2014, 21 citations), demonstrates her expertise in combining adaptive neural networks with robust control techniques. In her notable 2011 paper on fuzzy terminal sliding mode control for robot arms actuated by pneumatic artificial muscles (7 citations), she introduced an innovative approach that effectively mitigates the chattering problem inherent in terminal sliding mode control through fuzzy logic integration. Her 2013 work on neural network sliding mode control for underactuated manipulators (6 citations) further advances adaptive control by employing radial basis function neural networks as estimators to approximate system uncertainties. Mahjoub's contributions are particularly valuable for researchers working on soft robotics, rehabilitation devices, and precision control of underactuated mechanical systems, where her hybrid intelligent control approaches offer practical solutions for real-world implementation challenges.
Research Focus
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Top Papers
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