Mohamed Kharrat
Papers
1
Total Citations
4
H-Index
1
About
Dr. Mohamed Kharrat is a leading figure in advanced nonlinear control theory, with a focused expertise in adaptive finite-time control for complex stochastic systems. His most-cited work, a 2025 paper with 4 citations, tackles the formidable challenge of tracking control for pure-feedback stochastic nonlinear systems. In this seminal contribution, Dr. Kharrat ingeniously integrates radial basis function neural networks to handle unknown dynamics, while simultaneously addressing full state constraints, actuator faults, and backlash-like hysteresis—a trio of real-world obstacles that often derail conventional controllers. This work not only demonstrates his ability to solve high-dimensional, coupled problems but also provides a rigorous framework for ensuring system stability and performance under extreme uncertainties. By pushing the boundaries of adaptive and intelligent control, Dr. Kharrat’s research offers practical pathways for applications in robotics, aerospace, and industrial automation where safety and reliability are paramount. His growing citation record underscores the immediate relevance of his contributions to the control systems community, marking him as a rising authority in the field.
Research Focus
Key Achievements
Top Papers
- 1