Karim Gasmi
Papers
1
Total Citations
14
H-Index
1
About
Karim Gasmi is a rising researcher in the field of nonlinear control systems, with a focused expertise in adaptive neural network control and intelligent automation. His most cited work, published in 2023, addresses a critical challenge in robotics: compensating for unknown backlash-like hysteresis and bounded disturbances in nonlinear systems. By integrating radial basis function neural networks (RBFNN) with an adaptive command filter control approach, Gasmi developed a robust framework that ensures system stability and precision, with direct application to single-link robot manipulators. This contribution, already garnering 14 citations, demonstrates his ability to bridge theoretical control theory and practical mechatronic implementation. Gasmi’s research is particularly notable for tackling the complex, nonstrict-feedback dynamics that often hinder real-world robotic performance. His work not only advances the design of intelligent controllers but also provides a scalable solution for industrial automation and human-robot interaction systems. As his citation count grows, Gasmi is establishing himself as a key voice in adaptive control, offering students and engineers a pathway to more resilient and autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
- 1