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Robust neural control for robotic manipulators. (English) Zbl 0991.93080
Summary: A robust neural control scheme for mechanical manipulators is presented. The design basically consists of an adaptive neural controller, which implements a feedback linearization control law for a generic manipulator with unknown parameters, and a sliding-mode control, which robustifies the design and compensates for the neural approximation errors. It is proved that the resulting closed-loop system is stable and that the trajectory-tracking control objective is achieved. Some simulation results are also provided to evaluate the design.

93C85 Automated systems (robots, etc.) in control theory
70E60 Robot dynamics and control of rigid bodies
93B12 Variable structure systems
93B20 Minimal systems representations
Full Text: DOI
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