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About

Mohamed Benouaret is a control systems and robotics researcher whose work focuses on the stabilization and tracking control of complex, nonlinear, underactuated systems. His primary research areas include parallel robotics, intelligent control, and mechatronic system design, with a particular emphasis on the ball-on-plate problem—a classic benchmark for testing advanced control algorithms. Benouaret’s major contributions involve the development and implementation of hybrid control strategies that combine classical, fuzzy, and adaptive neuro-fuzzy inference systems (ANFIS) to achieve precise trajectory tracking and balance. His most cited work, "Tracking control of a ball on plate system using PID controller and Lead/Lag compensator with a double loop feedback scheme" (2021, 7 citations), demonstrates a practical approach to maintaining stability in a 6-DOF parallel robot. He has also pioneered the use of ANFIS-based multi-tasking algorithms for system stabilization, as seen in his 2022 paper. Despite the niche nature of his field, his publications have garnered citations from researchers working on parallel manipulators, humanoid robots, and drone stabilization, highlighting the broader applicability of his methods to modern robotics challenges.