Faouzi Bouani
Papers
8
Total Citations
81
H-Index
6
About
Faouzi Bouani is a control systems researcher whose work sits at the intersection of model predictive control (MPC), robotics, and intelligent autonomous systems. His research spans robotic manipulation, mobile robot navigation, rehabilitation robotics, and networked multi-agent systems, with a consistent focus on translating advanced control theory into real-world embedded implementations. Bouani's most influential contribution — a fast nonlinear MPC framework for parallel manipulators (2022, 29 citations) — demonstrates his ability to bridge computational efficiency with high-performance robotic control. His work on mobile robots has been equally prolific, addressing trajectory tracking using both kinematic and dynamic models, PSO-based path planning with camera vision, and real-time constrained MPC deployment on wheeled platforms. Notably, he has extended these methods into the Internet of Things domain, designing wireless networked predictive controllers for cooperative multi-agent systems operating under imperfect communication conditions. In rehabilitation engineering, Bouani has pioneered embedded MPC solutions for elbow joint orthosis robots, incorporating Hildreth's quadratic programming solver to handle the hard and soft constraints critical to patient safety. His adaptive PID work for non-square linear parameter-varying systems further underscores his breadth across control methodologies. With over 80 cumulative citations, his research offers valuable frameworks for students pursuing autonomous robotics, embedded control, and human-robot interaction.
Research Focus
Key Achievements
Top Papers
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- 3Predictive Control of Mobile Robot Using Kinematic and Dynamic Models12 citations · 2017
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