Max Robotics — Global Service Robot Directory + US Certification

About

Samir Bouzoualegh is a control systems researcher whose work centers on the application of advanced control strategies to robotic systems, with a particular focus on Model Predictive Control (MPC) and optimal control techniques. His research addresses one of the fundamental challenges in robotics: the inherently nonlinear nature of robotic dynamic models. Bouzoualegh has developed a systematic methodology that combines feedback linearization and input-output linearization techniques to transform complex nonlinear robot models into tractable linear systems, upon which sophisticated MPC frameworks can then be applied. His most impactful contribution, a comparative study of MPC and Linear Quadratic (LQ) optimal control for a two-link robot arm, has garnered 42 citations, establishing him as a credible voice in comparative control system analysis. His 2018 body of work was particularly productive, yielding three notable publications covering both manipulator arms and differential-drive mobile robots, collectively accumulating nearly 90 citations. He subsequently extended this framework to three-degrees-of-freedom manipulators, introducing refined cost function formulations. Bouzoualegh's research provides students and engineers with practical, reproducible control design pipelines for robotic platforms, making his work an accessible and valuable reference in the robotics control literature.