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.
The paper presents the application of the tensor product (TP)‐based model transformation technique to model and control the cart position of single‐input multi‐output pendulum‐cart systems (PCSs). The modeling is first carried out. The derived TP model, the nonlinear model of PCS, and the laboratory equipment are tested in the same open‐loop scenario, and their corresponding outputs are collected,...
This paper presents an application of the Tensor Product-based model transformation to the real-time position control of magnetic levitation systems. Three cases that depend on the number of singular values are presented. All case studies are validated by experiments conducted related to the sphere position control of a laboratory magnetic levitation system.
Our goal is to study numerical approximations of the solutions of backward stochastic differential equations in some general conditions for the coefficient functions and without the condition of the continuity for the final data. An example which sustains our explicitly scheme for solving a class of this stochastic differential equation is presented.
We propose a method for numerical approximation of the solutions of backward stochastic differential equations in some non-lipschitz conditions for the coefficient functions and without the condition of the continuity for the final data. Given a simulation-based estimator of the conditional expectation operator, we then suggest a backward simulation scheme. Our explicitly method is simple to implement...
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.