This overview focuses on model based control strategies for ventilation in nearly zero energy buildings (nZEB) where slower reactions towards disturbances are expected as a result of high insulation and air tightness of the building envelope (Killian and Kozek 2016). Furthermore, internal heat gains have a higher impact in these kind of buildings. In addition, occupancy pattern can be variable (e.g. in office- and school buildings) and HVAC control is consequently more challenging. In addition, there can be a discrepancy between the heating demand and ventilation demand with all-air ventilation systems. All these conditions imply that the internal environmental quality (IEQ) is a challenge to control in nZEB buildings. A model predictive control (MPC) approach could be a solution as it takes into account the current situation and the future disturbances and demand (Killian and Kozek 2016). Inside the MPC framework, state estimation is performed to predict the future states of a system and/or building. Based on these predictions the controller can set output values by solving an optimization problem. For the optimal control problem an objective is defined and constraints are set so also future disturbances are included. The objective is a cost function that minimizes typically the energy use with respect to the (thermal) comfort included in the cost function or defined as a constraint. The optimal control problem optimizes output values using the identified model to verify the solution.