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About

Walid Benaziza is a robotics and control systems researcher whose work centers on advanced motion control strategies for wheeled mobile robots, with a particular emphasis on trajectory tracking under real-world constraints. His research portfolio demonstrates a systematic progression from foundational sliding mode techniques to sophisticated hybrid intelligent control frameworks. In his most-cited work (2017, 14 citations), Benaziza proposed a terminal sliding mode approach combining quasi and global sliding mode controllers to achieve asymptotically stable angular error convergence, establishing a robust baseline for mobile robot guidance. Building on this, his 2016 contribution (11 citations) introduced a PID fast terminal sliding mode inverse dynamic control method designed to address the inherent nonlinear and nonholonomic challenges of mobile robot modeling. Benaziza has further advanced the field by integrating intelligent computing paradigms into control design, developing fuzzy sliding mode controllers for disturbance rejection and neural network-enhanced global fast sliding mode strategies that fuse kinematic and dynamic control layers. His work with RBF neural networks demonstrates a commitment to adaptive, computationally efficient solutions. With over 34 cumulative citations, Benaziza's contributions offer students and practitioners valuable frameworks for building resilient, high-performance autonomous mobile robot systems.