Sam Ziamanesh
Papers
1
Total Citations
2
H-Index
1
About
Sam Ziamanesh’s research focuses on advanced control systems for nonlinear robotic manipulators, with a particular emphasis on integrating bio-inspired optimization algorithms to enhance controller performance. In his most-cited work, "Parameter Tuning of Discontinues Lyapunov Based Controller Based on the Gray Wolf Optimization Algorithm Applied to a Robotic Manipulator" (2022), Ziamanesh tackles the challenge of stabilizing a nonlinear 2-Degree-of-Freedom robotic arm. By combining a discontinuous Lyapunov-based controller with the Gray Wolf Optimization algorithm, he demonstrates a novel method for fine-tuning control parameters, achieving superior robustness compared to traditional Proportional Integral Derivative with gravity compensation controllers. This work, while still early in its citation impact (2 citations), showcases his ability to bridge theoretical control theory and practical robotic applications. Ziamanesh’s contributions lie at the intersection of nonlinear dynamics, optimization, and robotics, offering a pathway toward more adaptive and reliable robotic systems. His research holds promise for advancing autonomous manipulation in industrial and service robotics, making him a rising voice in the field of intelligent control systems.
Research Focus
Key Achievements
Top Papers
- 1