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, iterative learning control (ILC) is applied to network-based control problems in which communication channels are subject to random transport delay and data dropout. An averaging ILC algorithm is used to overcome the random factors. Through analysis, it is shown that ILC can perform well and achieve asymptotical convergence in ensemble average along the iteration axis, as far as the...
In this work we focus on iterative learning control (ILC) for iteratively varying reference trajectories which are described by a high-order internal models (HOIM) that can be formulated as a polynomials between two consecutive iterations. The classical ILC with iteratively invariant reference trajectories, on the other hand, is a special case of HOIM where the polynomial renders to a first-order...
In our previous works, based on characteristics of emergency systems such as quick response to emergencies, a polynomial time algorithm was proposed to solve task schedulable problem. However, the above mentioned task scheduling method did not consider importance and urgency differences among tasks in selecting task to accomplish. In order to make the task scheduling be more close to actual process...
In this work we focus on iterative learning control (ILC) for iteratively varying reference trajectories which are described by a high-order internal model. The high-order internal model (HOIM) is formulated as a polynomial between two consecutive iterations. The classical ILC with iteratively invariant reference trajectories, on the other hand, is a special case of HOIM where the polynomial renders...
Loss tomography aims to obtain the loss rate of each link in a network by end-to-end measurements. If knowing the loss model of a link, we deal with a parametric estimate problem with incomplete data. Maximum likelihood estimate (MLE) is often used in this situation to identify the unknown parameters in the loss model, but it relies on the iterative approximation to identify the parameters that requires...
Video image matching to find tie points is one of important steps for merging dynamic, narrow field-of-view aerial video into a mosaic orthoimage. Because of its high data sampling rates and inherent characteristics of inconsistent and unstable flying of low-cost unmanned aerial vehicle (UAV), automatically matching of video data is still a big challenge and ongoing effort. This paper presents a self-adaptive...
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.