Papers
12
Total Citations
196
H-Index
8
About
El-Hadi Guechi is an accomplished control systems researcher whose work sits at the intersection of robotics, intelligent control, and autonomous navigation. His research primarily focuses on the modeling and control of mobile robots and robotic manipulators, with particular expertise in Model Predictive Control (MPC), Parallel Distributed Compensation (PDC), and Takagi-Sugeno (T-S) fuzzy systems. Guechi has made significant contributions to addressing practical challenges in robotic control, including handling nonlinear dynamics, sensor delays, and real-world motion constraints. His widely cited 2010 paper on PDC control for non-holonomic wheeled mobile robots with delayed outputs (52 citations) established an early foundation for his research trajectory. His prolific 2018 output, comparing MPC and LQ optimal control for robotic manipulators (42 citations), demonstrated his commitment to rigorous comparative analysis and feedback linearization techniques applicable to multi-link robot arms and differential-drive platforms. Beyond manipulation, Guechi has tackled autonomous navigation challenges, proposing innovative online obstacle avoidance strategies using piecewise Bézier curves. His body of work, accumulating nearly 200 citations, reflects sustained relevance across mobile robotics and industrial manipulator control, making his research particularly valuable for engineers and students working on advanced robotic control system design.
Research Focus
Key Achievements
Top Papers
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- 3Model predictive control of a two-link robot arm24 citations · 2018
- 4Model Predictive Control of a Differential-Drive Mobile Robot23 citations · 2018
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- 7Model Predictive Control of a Three Degrees of Freedom Manipulator Robot8 citations · 2019
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