This paper addresses the problem of self-triggered state-feedback control for linear plants under bounded disturbances. In a self-triggered scenario, the controller is allowed to choose when the next sampling time should occur and does so based on the current sampled state and on a priori knowledge about the plant. Besides comparing some existing approaches to self-triggered control available in the literature, we propose a new self-triggered control strategy that allows for the consideration of model-based controllers, a class of controllers that includes as a special case static controllers with a zero-order hold of the last state measurement. We show that our proposed control strategy renders the solutions of the closed-loop system globally uniformly ultimately bounded. We further show that there exists a minimum time interval between sampling times and provide a method for computing a lower bound for it. An illustrative example with numerical results is included in order to compare the existing strategies and the proposed one.