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About

Dr. Redha Rebhi is a control systems and robotics researcher whose work focuses on solving the trajectory tracking and path control challenges of wheeled mobile robots (WMRs). His core research integrates advanced control theory with meta-heuristic optimization, specifically developing hybrid controllers that combine backstepping techniques with fractional order PID (FOPID) and adaptive neuro-fuzzy inference systems (ANFIS). Dr. Rebhi’s major contributions include the design of an optimal backstepping-FOPID controller (11 citations), which addresses the difficult task of parameter tuning using hybrid optimization algorithms. He further advanced the field by creating a combined ANFIS-PID with backstepping technique (5 citations), merging neural-fuzzy adaptability with classical control for improved dynamic response. Notably, his experimental study on low-cost hardware implementation of a hybrid FOPID-backstepping controller (2 citations) demonstrates his commitment to bridging theoretical design with real-world application, featuring a self-designed, cost-effective mobile robot prototype. Through this work, Dr. Rebhi is making sophisticated control strategies more accessible and practical for autonomous mobile systems.