Mohammad Reza Shokoohinia
Papers
2
Total Citations
19
H-Index
2
About
Mohammad Reza Shokoohinia is a robotics and control systems researcher whose work centers on advanced nonlinear control strategies for robotic manipulators. His primary research areas include robust and adaptive sliding mode control, uncertainty estimation, and the application of Fourier series expansion techniques to improve robotic system performance. Shokoohinia’s major contributions lie in developing dynamic sliding mode control approaches that effectively handle system uncertainties and disturbances, ensuring precise and stable robot manipulation. His most cited paper, "Robust dynamic sliding mode control of robot manipulators using the Fourier series expansion" (2018, 12 citations), introduces a novel voltage-based control strategy that estimates uncertainties via Fourier series, compensating for truncation errors to enhance robustness. Another influential work, "Design of an adaptive dynamic sliding mode control approach for robotic systems via uncertainty estimators with exponential convergence rate" (2020, 7 citations), further advances the field by achieving faster, more reliable convergence. These contributions demonstrate Shokoohinia’s impact on improving the reliability and efficiency of electrically driven robotic systems, making his research valuable for students and engineers working on real-world robotic applications.
Research Focus
Key Achievements
Top Papers
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