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Nonlinear system adaptive trajectory tracking by dynamic neural control

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2 Author(s)
E. N. Sanchez ; CINVESTAV, Guadalajara, Mexico ; M. A. Bernal

In this article, new nonlinear control techniques based on dynamic neural networks are presented. The authors discuss the implementation of a modified identification algorithm using dynamic neural networks as well as a control law, based on the neural identifier, which eliminates modeling error effects via sliding mode techniques. Simulation and real time results are presented for systems like an inverted pendulum and a full actuated robot manipulator

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Neural Networks, 1999. IJCNN '99. International Joint Conference on  (Volume:3 )

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