This paper proposes a new robust control method for space robot by using neural network. A radial-basis-function (RBF) neural network is included to compensate for the system uncertainties. The parameters of the neural network are adapted on-line according to derived learning algorithms using Lyapunov method. Simulation results of a two-link planar space robot verify the validity of the proposed controller in the presence of uncertainties.
Robust tracking control of space robot via neural network
2006-01-01
1683389 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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