Sharifuddin Mondal
Pohang University of Science and Technology, Concordia University
Papers
2
Total Citations
95
H-Index
2
About
Sharifuddin Mondal is a control systems researcher whose work bridges robust estimation and robotic navigation. His most influential contribution, the 2010 paper "LMI approach to robust unknown input observer design for continuous systems with noise and uncertainties," has earned 74 citations and provides a powerful framework for state estimation in the presence of unknown disturbances—a critical tool for safety-critical systems. Complementing this theoretical work, Mondal has made significant practical advances in mobile robotics through his research on odometry calibration. His 2010 paper on terminal iterative learning control (TILC) for systematic odometry error correction (21 citations) addresses a fundamental challenge in robot navigation: without accurate odometry, even the best control algorithms fail. By applying iterative learning control to systematically reduce these errors, Mondal has helped enable more reliable autonomous navigation. His work is notable for connecting rigorous control-theoretic methods (LMIs, unknown input observers) with real-world robotic applications, demonstrating how advanced control theory can solve practical engineering problems. For students and researchers, Mondal's research exemplifies the powerful synergy between robust estimation theory and autonomous systems.
Research Focus
Key Achievements
Top Papers
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