Papers
8
Total Citations
85
H-Index
6
About
Mohamed Benrabah’s research lies at the intersection of continuum robotics, intelligent control systems, and autonomous vehicle navigation—fields where he has made impactful contributions through innovative, AI-driven solutions. His work on continuum robot manipulators is particularly notable; he developed optimized nonlinear sliding mode controllers and leveraged artificial neural networks to solve complex inverse kinematic models for both spatial and planar variable-curvature robots. These advances have been cited over 40 times collectively, with his 2022 paper on optimized nonlinear sliding mode control alone garnering 18 citations. Benrabah has also pioneered adaptive control strategies, including a Fourier series neural network PID controller, and introduced constrained nonlinear predictive control frameworks that integrate teaching-learning-based optimization and Archimedes optimization algorithms. In the domain of autonomous ground vehicles, he has advanced traversability risk assessment by proposing dual occupancy and knowledge maps management systems, as well as authoring a comprehensive review on risk assessment methods and metrics. His work bridges theoretical modeling with practical robotic control, earning recognition for its originality and applicability in both soft robotics and autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1Optimized Nonlinear Sliding Mode Control of a Continuum Robot Manipulator18 citations · 2022
- 2Adaptive Fourier Series Neural Network PID Controller16 citations · 2021
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