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.
When an model predictive controller (MPC) is subject to unbounded uncertainty, it is generally impossible to guarantee resolvability or recursive feasibility. In our previous work we developed an open-loop chance-constrained model predictive control (CCMPC) algorithm that is probabilistically resolvable [1], meaning that, given a feasible solution at the current time, the controller is guaranteed...
Resolvability or recursive feasibility is an essential property for robust model predictive controllers. However, when an unbounded stochastic uncertainty is present, it is generally impossible to guarantee resolvability. We propose a new concept called probabilistic resolvability. A model-predictive control (MPC) algorithm is probabilistically resolvable if it has feasible solutions at future time...
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.