Hassan Bayani
Papers
6
Total Citations
97
H-Index
5
About
Hassan Bayani’s research focuses on the modeling, control, and optimization of cable-driven parallel robots (CDPRs) and novel spherical rolling robots. His major contributions include pioneering vision-based control and identification for planar CDPRs, developing robust neuro-adaptive controllers that integrate neural-network estimators with radial basis functions to handle system uncertainties, and advancing computed torque control methods to ensure tensile cable forces during motion. Bayani also made significant strides in workspace analysis, proposing convex optimization techniques to determine maximal inscribed ellipsoids within the wrench-feasible workspace, thereby enhancing robot design and performance. His work on adaptive sliding mode controllers for spherical rolling robots further demonstrates his versatility in addressing complex robotic challenges. With his most-cited paper garnering 52 citations, Bayani’s research has had a tangible impact on the field, providing foundational insights for both theoretical advancements and practical implementations. His studies on classic controller tuning with intelligent algorithms offer accessible solutions for optimizing CDPR performance, making his contributions valuable for students and researchers exploring robust control strategies and workspace optimization in robotics.
Research Focus
Key Achievements
Top Papers
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- 3Computed torque control of a cable suspended parallel robot10 citations · 2015
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