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Adaptive motion control using neural network approximations

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Abstract
In this paper, we present a new adaptive technique for tracking control of mechanical systems in the presence of friction and periodic disturbances. Radial Basis Functions (RBFs) are used to compensate for the effects of nonlinearly occurring parameters in the friction and periodic disturbance model. Theoretical analysis, such as stability and transient performance, is provided. Furthermore, the performance of the adaptive RBF controller and its non-adaptive counterpart are compared. © 2001 Elsevier Science Ltd. All rights reserved.
Keywords
Adaptive control, Compensation, Friction, Neural networks, Uncertainty
Source Title
Automatica
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Date
2002-02
DOI
10.1016/S0005-1098(01)00192-3
Type
Article
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