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
01.01.2006
1683389 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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