Papers
5
Total Citations
113
H-Index
4
About
Slim Dhahri is a control systems researcher whose work sits at the intersection of robust control theory, fault estimation, and nonlinear systems engineering. His research focuses primarily on sliding mode control design, fault-tolerant control, and observer-based methodologies for uncertain nonlinear systems, with a particular emphasis on Takagi–Sugeno fuzzy representations and Linear Matrix Inequality (LMI) optimization techniques. Dhahri's most influential contribution — his 2012 work on robust H∞ sliding mode observer design for fault estimation, which has accumulated 66 citations — established a rigorous framework for detecting and estimating faults in uncertain nonlinear systems, a critical challenge in modern control engineering. Building on this foundation, he has pioneered hybrid control strategies that combine integral sliding mode control with optimal feedback laws to address both matched and unmatched uncertainties, and has extended these approaches to adaptive fault-tolerant designs capable of handling multiplicative faults. His 2019 work on wheeled mobile robot trajectory tracking further demonstrates his commitment to translating theoretical advances into practical robotics applications. Across his body of work, Dhahri has consistently advanced the reliability and robustness of control systems, making his research particularly valuable to engineers and researchers working on safety-critical and autonomous systems.
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