Chin-Pao Hung

National Chin-Yi University of Technology, National Taiwan University of Science and Technology

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About

Chin-Pao Hung specializes in robotics control systems, embedded system design, and neural network-based control. His research focuses on making robotic systems more intuitive and accessible through innovative teaching methods. Hung’s most significant contributions include developing an embedded teaching system for multi-jointed robots that uses I2C communication protocol. Unlike traditional teaching panels requiring complex coordinate transformation computations, his approach allows operators to simply drag a teaching robot to demonstrate desired motions—a more intuitive and simpler scheme. This work has been cited 4 times each in two related publications from 2012. Earlier, Hung made contributions to variable structure control of DC servo systems with unknown parameters, using a CMAC-based learning approach with a compensating neural network. Published in 2001, this work also received 4 citations and introduced a stabilizer controller combined with a CMAC neural network to construct effective control laws. Through these contributions, Hung has advanced the fields of robot teaching systems and adaptive control, offering practical solutions that reduce complexity while maintaining robust performance.