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
Conference paper
Electronic Resource
English
Robust Adaptive Neural-Fuzzy Network Tracking Control for Robot Manipulator
BASE | 2014
|Robust tracking control of electrical driven free-floating space robot manipulators
Tema Archive | 2006
|Neural Network Robust Control of Ship Trajectory Tracking
British Library Conference Proceedings | 2014
|Robust trajectory tracking control of a dual-arm space robot actuated by control moment gyroscopes
Online Contents | 2017
|