Saba Ghorbani Barzegar
Papers
1
Total Citations
1
H-Index
1
About
Saba Ghorbani Barzegar is a robotics researcher specializing in advanced control systems for autonomous mobile platforms, with a primary focus on trajectory tracking and stability under real-world uncertainties. Her most cited work, "Adaptive Sliding Mode Control for Trajectory Tracking in Four-Wheeled Mobile Robots Under Uncertainties and External Disturbances," introduces a novel adaptive sliding mode control (SMC) design that dynamically adjusts to model uncertainties and external perturbations, significantly enhancing the stability and precision of skid-steering robots. This contribution addresses critical challenges in field robotics, where unpredictable terrain and disturbances often compromise performance. By integrating adaptive rules into the SMC framework, her approach ensures robust trajectory tracking without requiring precise prior knowledge of system dynamics. Though early in her career, her work has already garnered citations, reflecting its relevance to researchers tackling similar control problems. Ghorbani Barzegar’s research sits at the intersection of nonlinear control theory and practical robotics, offering scalable solutions for autonomous navigation in agriculture, search-and-rescue, and industrial automation. Her methodology provides a foundation for future work on adaptive and resilient robotic systems.
Research Focus
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Top Papers
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