Journal
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volume 54, Issue 3, Pages 1763-1767Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2007.894706
Keywords
actuator nonlinearity; dc motor system; neural networks (NNs); saturation compensation; stability
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A neural network (NN) saturation compensation scheme for dc motor systems is presented. The scheme, which leads to stability, command following, and disturbance rejection, is rigorously proven. The online weight tuning law, overall closed-loop performance, and boundness of the NN weights are derived and guaranteed based on the Lyapunov approach. Simulation and experimental results show that the proposed scheme effectively compensates for saturation nonlinearity in the presence of system uncertainty.
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