Mohammad Bagher Abolhasani Jabali
Papers
3
Total Citations
38
H-Index
3
About
Mohammad Bagher Abolhasani Jabali is a researcher specializing in advanced control systems for robotic manipulators, with a particular focus on polytopic Linear Parameter Varying (LPV) modeling and robust trajectory tracking. His work addresses the fundamental challenge of controlling highly nonlinear robotic systems by developing systematic, model-based approaches that improve both stability and performance. His most influential paper, "Uncertain polytopic LPV modelling of robot manipulators and trajectory tracking" (2017), has accumulated 28 citations and introduces a framework for handling parametric uncertainties in robot dynamics. In a subsequent contribution, "State-feedback control of robot manipulators using polytopic LPV modelling with fuzzy-clustering" (2018), he proposed a novel algorithm that integrates fuzzy clustering with LPV modeling to enable full state-feedback control design. This approach linearizes the Lagrangian dynamics around a desired trajectory, allowing for more practical and computationally efficient controller synthesis. Though his citation counts are still growing, Abolhasani Jabali's work represents a meaningful step toward bridging theoretical robust control with real-world robotic applications, offering tools that are both rigorous and implementable for researchers working on nonlinear robot control.
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