The paper presents an optimization-based approach to compute controllers for a class of hybrid systems with switched dynamics. The starting point is a representation as a hybrid automaton which models autonomous switching between different nonlinear dynamics and includes discrete as well as continuous control inputs. The automaton is transformed into a linear discrete-time model in equation-based form. The task of generating an optimal control law to drive the system from an initial state into a target region (while avoiding forbidden states) is solved by mixed-integer programming performed in a moving-horizon setting with variable time steps.