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.
This paper concerns the control law design by variable structure control for a kind of uncertain discrete-time systems. Why the chattering shows up for this kind of systems by discrete reaching law is investigated, and then a developed variable structure controller is designed based on grey prediction iterative algorithm. Based on the grey prediction model, the parameter values are obtained. A criterion...
This paper develops a hierarchical gradient-based iterative estimation algorithm for multi-input multi-output output error moving average (OEMA-like) models. In order to solve the difficulties that the noise-free outputs and the noise terms in the information vector/matrix of the corresponding identification model are unmeasurable, we replace the unknown variables in the information vector/matrix...
This paper derives a least squares based and a gradient based iterative identification algorithms for Wiener nonlinear systems. These methods separate one bilinear-parameter cost function into two linear-parameter cost functions, estimating directly the parameters of the Wiener systems. The simulation results confirm that the proposed two algorithms are valid and the least squares based iterative...
A gradient-based iterative (GI) identification algorithm is developed for Box-Jenkins systems (or models) with finite measurement input-output data. Compared with the pseudo-linear regression stochastic gradient approach, the proposed algorithm updates the parameter estimation using all the available data at each iterative computation (at each iteration), and thus can produce highly accurate parameter...
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.