Mohammad Hassan Shojaeefard

Iran University of Science and Technology

Papers

Total Citations

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About

Mohammad Hassan Shojaeefard is a researcher whose work sits at the intersection of robotics, control systems, and artificial intelligence. His research focuses primarily on the development of advanced control strategies for autonomous and car-like robotic systems, with a particular emphasis on addressing real-world challenges such as model uncertainties, disturbances, and trajectory tracking accuracy. Among his most notable contributions is his work on adaptive fuzzy nonlinear sliding-mode controllers, which enable robotic systems to update their control parameters online using fuzzy logic — a significant advancement that enhances robustness against unpredictable environmental conditions. His 2019 paper on this topic has garnered 14 citations, reflecting meaningful engagement from the control systems research community. Complementing this, his work integrating indirect radial-basis-function neural networks with adaptive fuzzy sliding mode control further demonstrates his commitment to intelligent, data-driven approaches for autonomous vehicle navigation. Shojaeefard's research is particularly timely given the global urgency surrounding autonomous vehicle development and road safety. By designing controllers that mitigate human error through intelligent automation, his contributions hold practical implications for the future of driverless transportation. His body of work represents a promising bridge between theoretical control engineering and applied autonomous systems research.