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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.

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