Event-triggered control and sampled-data feedback stabilization of nonlinear systems. The constant evolution of digital technologies is based on the increasing usage of digital control systems. In this context, a control system is characterized by the digital computation of a control law from sampled measurements. In this subject, I focused in the sampled-data feedback stabilization of nonlinear systems. For a given increasing sequence of times, the control law is updated at each of those time instants and is fed into the system as a constant input until the next time instant when it is updated again. In [1, C1], we studied the semi-global stabilization of nonlinear systems by sampled-data feedback using certain asymptotic controllability conditions. The main results was the derivation of Lie-algebraic conditions for the semi-global asymptotic stabilization with sampled-data feedback for affine in the control nonlinear systems. Those conditions generalize the well-known Artestein-Sontag condition for asymptotic stabilization with almost smooth feedback. In [4, C2, C3, C4], I focused in the stabilization by sampled-data feedback by using event-triggered and self-triggered mechanisms. Event-triggered techniques use a mechanism to monitor the real-time state of the system and generate the sampling times only when necessary resulting in non-periodic controller updates. This methodology was applied in cascade connected systems as well as in interconnected systems in [C2, C4] with immediate applications in multi-agent systems, networked control systems and vehicle platoons. Finally, in [4, C3] we studied the self-triggered stabilization with time-delays where the next controller update time is generated based on the last measurement of the system’s state and does not require continuous monitoring of the system's state.