Papers
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Total Citations
2
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About
Kwang-Bo Cho is a researcher whose work lies at the intersection of neural control systems and robotics. His key research areas include intelligent control architectures, neural network-based system identification, and adaptive robotic manipulation. Cho's major contribution is the development of a feedforward/feedback neural control structure that integrates a neural identifier with multiple controller blocks—a feedforward controller for computed torque generation, a PD controller, and a multilayer neural controller for compensation. This innovative architecture enables robots to learn and adapt their movements in real time, improving precision and stability in dynamic environments. While his most cited paper, "A feedforward/feedback neural control structure and its application to a robotic system" (2005), has garnered 2 citations, its conceptual framework has influenced subsequent work in neural adaptive control. Cho's research demonstrates a thoughtful approach to combining classical control theory with modern machine learning, offering practical solutions for robotic systems that require both accuracy and adaptability. His work remains relevant for researchers exploring bio-inspired control strategies and intelligent automation.
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