Peng Tan

Papers

Total Citations

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About

Peng Tan is a robotics researcher whose work focuses on the critical challenge of precision control in high-inertia robotic systems. His most-cited paper, "Adaptive Trajectory Compensation of Large Inertia Robot" (2024), introduces novel algorithms that dynamically correct motion errors caused by mass and momentum in heavy-duty industrial robots. This contribution is vital for applications requiring millimeter-level accuracy, such as automated manufacturing and aerospace assembly, where traditional fixed-gain controllers fail. Tan’s approach leverages real-time adaptive feedback to mitigate trajectory deviations, improving both operational safety and efficiency. While his citation count is still emerging—with 2 citations to date—the work represents a foundational step in bridging the gap between theoretical control theory and practical robotic deployment. Tan’s research is particularly notable for its emphasis on scalability, offering solutions that can be applied to robots ranging from collaborative arms to large-scale manipulators. As the demand for precise, heavy-load automation grows, Tan’s adaptive compensation techniques are poised to become a standard reference for engineers tackling inertia-induced instability. His work signals a promising trajectory in robotics, blending rigorous mathematical modeling with hands-on engineering insight.