Mahdi Bashari
Papers
1
Total Citations
4
H-Index
1
About
Mahdi Bashari is a researcher focused on the advanced control and estimation of robotic systems, with a particular emphasis on Cable-Driven Parallel Robots (CDPRs). His work addresses the critical challenge of robustly controlling these complex, nonlinear systems in the presence of sensor noise and dynamic uncertainties. In his most-cited paper, "Robust Optimal Control of Cable-Driven Parallel Robots with Moving Average Fading Memory Kalman Filter Observer" (2022), Bashari introduces a novel approach that transforms the nonlinear CDPR dynamics into a parameterized State-Dependent Coefficient (SDC) structure. This innovation allows for the implementation of linear filtering techniques, specifically a Moving Average Fading Memory Kalman Filter, which significantly enhances the observer’s ability to reject disturbances and improve control precision. With 4 citations, this work demonstrates his contribution to bridging theoretical control methods with practical robotic applications. Bashari’s research is instrumental for students and engineers working on high-performance automation, offering a pathway to more reliable and accurate control of cable-driven systems in industries like manufacturing, rehabilitation, and large-scale manipulation.
Research Focus
Key Achievements
Top Papers
- 1