Ali Akbar Pirmohamadi

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About

Ali Akbar Pirmohamadi is an emerging researcher specializing in advanced control systems for robotic manipulators, with a particular focus on parallel robot dynamics and trajectory tracking. His work addresses one of the most pressing challenges in modern robotics: achieving precise, robust control in the presence of complex dynamics, uncertainties, and real-world constraints. Pirmohamadi's most notable contribution, published in 2023 and accumulating 14 citations, introduces an optimal adaptive barrier-function super-twisting nonlinear global sliding mode control scheme for parallel robots. This innovative framework leverages the structural advantages of parallel robots — including superior rigidity, accuracy, and load-bearing capacity — while elegantly overcoming their inherently complex dynamics through intelligent adaptive mechanisms. Building on this foundation, his 2025 study advances the field further by developing an adaptive barrier terminal sliding mode approach that explicitly handles input saturation and external disturbances, ensuring finite-time convergence and improved transient performance under practical constraints. Together, these contributions reflect a coherent research vision aimed at bridging theoretical control design with real-world robotic applicability. Pirmohamadi's work is particularly valuable for researchers and engineers seeking reliable, high-performance solutions for parallel manipulator systems operating in demanding environments.