Title: Symbolic control of nonlinear systems – safety, optimization and learning

Abstract: Symbolic control is a computational approach to control nonlinear systems subject to state and input constraints. It is based on the use of symbolic models that are sound discrete-state approximations of the original dynamics. Symbolic models can be used to synthesize automatically controllers for the original system while providing safety guarantees. In the first part of the tutorial, I will give a short introduction to the field of symbolic control covering topics such as computation of symbolic models or synthesis of discrete controllers. The second part of the tutorial will be devoted to more recent developments. I will show how symbolic control and optimization-based control can be combined to design controllers with safety guarantees and optimized performance. I will also present recent approaches to compute symbolic models directly from data, paving the way to the development of safe learning approaches for nonlinear systems.