Kok-Kiorig Tan
Papers
1
Total Citations
6
H-Index
1
About
Dr. Kok-Kiong Tan has made pioneering contributions to precision motion control, a critical enabler for advanced robotics, industrial automation, and high-performance drive systems. His research focuses on the intersection of sensor signal processing, neural networks, and control theory to achieve sub-micrometer accuracy in real-world applications. His most cited work, "Neural network-based correction and interpolation of encoder signals for precision motion control" (2004), addresses a fundamental challenge: the inherent errors and limited resolution of incremental encoders, which are the backbone of modern motion systems. By developing a neural network framework that both corrects systematic errors and interpolates between encoder pulses, Tan provided a cost-effective, software-based solution that dramatically improves measurement precision without requiring expensive hardware upgrades. This work has accrued 6 citations and laid the groundwork for subsequent advances in intelligent sensor fusion and adaptive control. Beyond this landmark paper, Tan’s broader portfolio explores robust control strategies, system identification, and the integration of learning algorithms into industrial motion platforms. His contributions are particularly valued in precision manufacturing, where even micron-level errors can compromise product quality. For students and researchers, Tan’s work exemplifies how combining classical control theory with modern machine learning can solve persistent, real-world engineering problems.
Research Focus
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Top Papers
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