Papers
22
Total Citations
225
H-Index
7
About
Nasser Sadati is a prominent researcher in robotics and intelligent control systems, whose work spans robotic manipulator control, motion planning, and legged locomotion. His research draws on a rich intersection of computational intelligence and control theory, employing tools such as neural networks, fuzzy logic, genetic algorithms, and sliding mode control to tackle complex robotic challenges. Sadati's most influential contribution, "Adaptive multi-model sliding mode control of robotic manipulators using soft computing" (2008), has garnered 72 citations, establishing him as a leading voice in adaptive control methodologies. His early work on robot motion planning, combining Hopfield neural networks with genetic algorithms in both crisp and fuzzified environments (2003), demonstrated creative problem-solving approaches that collectively attracted over 40 citations. His hierarchical and gradient-based frameworks for optimal control of robot manipulators further reflect a systematic approach to managing complex, large-scale robotic systems. Beyond manipulation, Sadati extended his expertise to bipedal locomotion, contributing analytical stabilization methods for planar walking robots and co-authoring the comprehensive volume *Hybrid Control and Motion Planning of Dynamical Legged Locomotion* (2012). Across his career, Sadati has consistently advanced intelligent, adaptive solutions to foundational robotics problems, making his work valuable reading for students and researchers in control engineering and autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 7A new hierarchical approach for optimal control of robot manipulators7 citations · 2005
- 8Hybrid Control and Motion Planning of Dynamical Legged Locomotion6 citations · 2012
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- 10Adaptive Fuzzy Decentralized Control of Robot Manipulators5 citations · 2006