Papers
2
Total Citations
16
H-Index
2
About
Xiaodan Chang is a researcher specializing in advanced control systems for heavy machinery, with a primary focus on friction compensation in excavator systems. Her work addresses the critical challenge of modeling and mitigating friction-induced inaccuracies in hydraulic and mechanical excavator components, which directly impacts operational precision and energy efficiency. Chang’s most cited paper, “Friction Compensation Control Method for a Typical Excavator System Based on the Accurate Friction Model” (2024, 14 citations), introduces a novel approach that integrates precise friction modeling with adaptive control strategies, significantly improving tracking accuracy and reducing wear in excavator joints. This contribution is foundational for the development of smarter, more reliable construction equipment. A related 2023 paper (2 citations) further refines these methods, demonstrating her sustained focus on this niche. Chang’s work has practical implications for automation in construction and mining, where precise control under variable loads is essential. Her research bridges theoretical control engineering and real-world machinery, offering scalable solutions for industry adoption.
Research Focus
Key Achievements
Top Papers
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