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.
We extend a recently developed design for indirect adaptive model predictive control (IAMPC) and presents additional results on its stability properties. The IAMPC guarantees constraints satisfaction including during the learning transient, is input-to-state stable (ISS) with respect to the parameter estimation error, and has computational burden comparable to that of non-adaptive MPC. In this paper...
In this paper, the robust state feedback stabilization of uncertain discrete-time constrained nonlinear systems in which the loop is closed through a packet-based communication network is addressed. In order to cope with model uncertainty, time-varying transmission delays, and packet dropouts (typically affecting the performances of networked control systems), a robust control scheme combining model...
The paper presents the algorithm in robust constrained model predictive control for uncertain piecewise affine with time-invariant state-delay system using saturated linear feedback controller. Polytopic uncertain piecewise affine with time-invariant state-delay system is considered, and polytopic description for saturated function is used in the formulation. The robust performance index is presented...
In this paper, we propose a robust constrained model predictive control (RCMPC) for stabilizing processes with norm-bounded uncertainty. This type of uncertainty is used to avoid on-line computational burdens. The robust stability comes with a guarantee described by parameter-dependent Lyapunov function (PDLF). The control law based on PDLF is potentially less conservative than that based on single...
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.