Elyes Maherzi
Papers
5
Total Citations
37
H-Index
3
About
Elyes Maherzi is a robotics researcher specializing in the control and trajectory generation of bipedal and anthropomorphic robots, with a particular focus on model predictive control (MPC) and robust dynamic control strategies. His most cited work, "Trajectory Generation using Predictive PID Control for Stable Walking Humanoid Robot" (2015, 20 citations), introduces a predictive control framework for generating stable walking trajectories, building on foundational work by Katayama and Kajita. Maherzi further advances the field through his contributions to robust control under uncertainty, as seen in his 2019 paper on synthesizing MPC controllers for uncertain systems subject to input and output constraints, applied to anthropomorphic robot arms. His research also explores switched control systems for compass gait biped robots and LMI-based robust dynamic controllers for improving walking stability using the Zero Moment Point criterion. With a cumulative citation count exceeding 35 across his key publications, Maherzi’s work is recognized for bridging theoretical control methods—such as convex optimization and linear matrix inequalities—with practical robotic applications, making significant strides toward more stable and reliable humanoid locomotion.
Research Focus
Key Achievements
Top Papers
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- 3Switched Control for the Walking of a Compass Gait Biped Robot3 citations · 2014
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