The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, we consider the friction compensation problem for a class of mechanical systems. The friction behavior is described by a nonlinear dynamical model. Since it is difficult to know the nonlinear parts in the frictional model accurately, two neural networks (NNs) are employed in the proposed intelligent controller. Due to the learning capability of the NNs, the designed NN controller can...
The paper deals with the problem of model reference adaptive control of a class of uncertain nonlinear systems by output feedback based on neural networks. The uncertainty of the system can not be parameterized and its upper bound is unknown. In order to approximate the uncertainty via neural networks, a technique of global approximation of continuous functions is introduced. Based on the technique,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.