Ali Khaki Sedigh

K.N.Toosi University of Technology

Papers

8

Total Citations

140

H-Index

6

About

Ali Khaki Sedigh is a distinguished researcher in the field of robotics and control systems, with a primary focus on adaptive control, nonlinear multi-agent systems, and teleoperation. His most influential work includes the development of an adaptive recurrent neural network with Lyapunov stability learning rules for robot dynamic term identification, which has garnered 44 citations and represents a significant contribution to intelligent robotic control. Dr. Khaki Sedigh has made substantial advances in bilateral control of master-slave manipulators under constant time delay, a critical challenge in teleoperation systems, with his 2011 paper earning 31 citations. His innovative switched logic-based control strategy for target tracking using range-only measurements, cited 27 times, has advanced autonomous robotic vehicle navigation. More recently, he has addressed consensus control problems in nonlinear multi-agent robot systems, developing fast terminal sliding mode control and leader-follower consensus strategies that account for external disturbances and input saturation. His work on predictive control for satellite tracking pedestals demonstrates practical applications in aerospace systems. With over 140 total citations across his publications, Dr. Khaki Sedigh continues to shape modern robotics through his contributions to adaptive control, multi-agent coordination, and teleoperation systems.

Research Focus

Key Achievements

6
H-Index
8
Papers
140
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
Adaptive recurrent neural network with Lyapunov stability learning rules for robot dynamic terms identification
44 citations · 2017
📈 Most Prolific Year: 2011 (5 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: K.N.Toosi University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago