Halim Merabti

About

Halim Merabti is a leading researcher in the intersection of advanced control theory and robotics, with a particular focus on nonlinear model predictive control (NMPC) and continuum robotics. His work addresses the fundamental challenge of applying computationally intensive predictive control algorithms to fast-moving and highly flexible robotic systems. Merabti’s major contributions include pioneering the use of metaheuristic optimization algorithms—such as particle swarm optimization—to solve NMPC problems in real time, enabling precise trajectory tracking for quadcopters, mobile robots, and continuum robots. His research on continuum robots, which mimic biological structures like elephant trunks and octopus arms, has advanced both kinematic and dynamic modeling, as well as inverse kinematics solutions for these complex, flexible systems. With over 100 citations across his most-cited works, Merabti’s impact is evident in his 2015 paper on quadcopter NMPC (32 citations) and his 2015 work on mobile robot predictive control (30 citations). His recent 2022 paper on continuum robot control (16 citations) and a 2023 bio-inspired dual-module continuum robot design demonstrate his ongoing innovation. Merabti’s work bridges the gap between theoretical control methods and practical robotic applications, making him a key figure in the development of agile, precise, and bio-inspired robotic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Nonlinear model predictive control of quadcopter

   32 citations · 2015
2. 2
   Nonlinear predictive control of a mobile robot: a solution using metaheuristcs

   30 citations · 2015
3. 3
   Nonlinear model predictive control of a class of continuum robots using kinematic and dynamic models

   16 citations · 2022
4. 4
   A new approach to solve inverse kinematics of a planar flexible continuum robot

   11 citations · 2014
5. 5
   Bio-inspired a novel dual-cross-module sections cable-driven continuum robot: design, kinematics modeling and workspace analysis

   8 citations · 2023
6. 6
   Performance evaluation of Particle Swarm Optimization variants for trajectory tracking of a cable-driven continuum robot: descriptive, parametric, and non-parametric statistical analysis

   4 citations · 2025
7. 7
   Multi-Objective Predictive Control : A Solution Using Metaheuristics

   3 citations · 2014
8. 8
   Accelerated micro particle swarm optimization for the solution of nonlinear model predictive control

   2 citations · 2017

Key Collaborators

Contact & Links