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About

Oussama Hadoune is a robotics and control systems researcher whose work focuses on the critical challenge of dynamic stabilization and precision tracking in nonlinear, underactuated systems. His research primarily explores the intersection of advanced control theory and parallel robotics, with a particular emphasis on the classic ball-on-plate problem—a benchmark for testing complex control algorithms. Hadoune’s major contributions include the development and comparative analysis of multiple control strategies for this system. He has designed and implemented a double-loop feedback scheme using PID controllers and Lead/Lag compensators for a ball-on-plate system (7 citations), demonstrating effective tracking control. He further advanced this work by integrating fuzzy logic with PID control for a 6-DOF parallel robot (3 citations), and introduced an adaptive neuro-fuzzy inference system (ANFIS) for multi-tasking stabilization on a 3-DOF parallel robot (2 citations). His notable achievement lies in the physical design and realization of these parallel robot platforms, bridging theoretical control algorithms with practical hardware implementation. Hadoune’s work provides valuable insights for researchers in humanoid robotics, drone stability, and any field requiring robust balance control.