Masih Sharifi
Papers
1
Total Citations
8
H-Index
1
About
Dr. Masih Sharifi is a control systems researcher whose work bridges the gap between classical robotics and intelligent optimization. His primary research areas include sliding mode control, fuzzy logic systems, and multi-objective evolutionary algorithms, with a particular focus on their application to robotic manipulators. His most influential contribution, the 2011 paper "Application of fuzzy sliding mode control to robotic manipulator using multi-objective genetic algorithm," has garnered 8 citations and pioneered a novel approach that integrates Fuzzy Sliding Mode (FSM) control with Genetic Algorithms to simultaneously optimize sliding parameters and fuzzy membership functions. This work is notable for addressing the inherent trade-offs in control system design—where improving one objective often degrades another—by leveraging multi-objective optimization to find Pareto-optimal solutions. Dr. Sharifi’s research demonstrates a sophisticated understanding of how intelligent control can enhance the robustness and precision of robotic systems, making his work a valuable reference for engineers and researchers working at the intersection of nonlinear control and computational intelligence.
Research Focus
Key Achievements
Top Papers
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