Jer-Guang Hsieh
Papers
1
Total Citations
6
H-Index
1
About
Jer-Guang Hsieh is a control systems researcher whose work focuses on adaptive control and neural network-based approaches for nonlinear systems. His most cited paper, "Adaptive tracking control of a class of nonlinear systems using CMAC network" (1996), introduced a novel framework that leverages the Cerebellar Model Articulation Controller (CMAC) network to achieve robust tracking in complex, nonlinear dynamics. This contribution, with 6 citations, laid groundwork for integrating neural architectures into adaptive control, addressing challenges in system uncertainty and real-time performance. Hsieh’s research bridges theoretical control design and practical implementation, emphasizing stability and convergence in adaptive algorithms. His work has influenced subsequent studies in intelligent control, particularly in robotics and automation, where CMAC networks offer computational efficiency. While his citation count reflects a focused niche, Hsieh’s early adoption of neural networks for control problems underscores his foresight in merging machine learning with classical control theory. For students and researchers, his paper remains a reference point for understanding adaptive tracking in nonlinear systems using biologically inspired models.
Research Focus
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Top Papers
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