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This paper describes an Adaptive Backstepping Neural Network (ABNN) method used for a ship course tracking control. The ship model is described by a third order nonlinear model whose parameters are unknown. The control design uses estimate values of unknown parameters of the system. Then, adaptive laws of the estimation of these values have been proposed. The stability of the controlled system has...
We address the problem of designing decentralized laws to control a team of general fully actuated manipulators which synchronize their movements while following the same desired trajectory. To this effect we investigate an adaptive control of an identical multiple manipulators, with unknown inertia parameters, tracking a common trajectory. It is also assumed that all the robots in the synchronization...
In this paper, an adaptive backstepping method is used for a ship course tracking control. This has been done by applying a reference signal derived from a LOS algorithm. The ship model is described by a third order nonlinear model whose parameters are unknown. The control design uses estimate values of the unknown parameters of the system. Then, adaptive laws of the estimation of these values have...
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