Papers
8
Total Citations
274
H-Index
8
About
Amin Jalali is a prominent researcher in the field of nonlinear control systems, with a particular focus on intelligent and robust control methodologies for robot manipulators and complex dynamic systems. His work sits at the intersection of classical control theory and soft computing, pioneering hybrid approaches that combine sliding mode control (SMC), fuzzy logic, and adaptive algorithms to address real-world uncertainties in robotic systems. Jalali's most impactful contributions include the development of model-free adaptive fuzzy sliding mode controllers optimized through particle swarm optimization (PSO), earning 56 citations, and adaptive fuzzy computed torque controllers for multi-degree-of-freedom manipulators, with 55 citations. These works tackled persistent challenges such as chattering phenomena and nonlinear dynamic uncertainty — longstanding obstacles in robust controller design. His 2011 paper introducing the AFGSMC framework (42 citations) further demonstrated his ability to bridge theoretical rigor with practical applicability. Beyond sliding mode approaches, Jalali made notable contributions to backstepping control, colonial competitive optimization, and continuum robot control, reflecting the breadth of his expertise. With over 270 cumulative citations across his top papers, his research has meaningfully advanced the development of intelligent, computationally efficient control strategies that remain highly relevant to robotics and automation engineering today.
Research Focus
Key Achievements
Top Papers
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- 3Artificial Control of Nonlinear Second Order Systems Based on AFGSMC42 citations · 2011
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- 5Artificial Robust Control of Robot Arm: Design a Novel SISO Backstepping Adaptive Lyapunov Based Variable Structure Control.34 citations · 2011
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