U ntil now, advanced model-based control techniques have been predominantly employed to control problems that are relatively straightforward to model. Many systems with complex dynamics or containing sophisticated sensing and actuation elements can be controlled if the corresponding mathematical models are available, even if there is uncertainty in this information. Consequently, the application of model-based control strategies has flourished in numerous areas, including indus-The difficulty arises when there are components in the controlled system that are not easily modeled in a standard setting. One important and broad class of such systems is when humans are involved in the actuation process, in measurements, or in system dynamics. How to integrate the important role played by human operators in the control problem formulation is still an open question. Control methods typically rely on a fully automatic control operation that, in the case of humans being involved in the control system, is unrealistic. Likewise, fully manual control methods might compromise the performance of the system because of factors such as limitations on the availability of the operators to implement control actions or the lack of coordination when several operators are involved. Therefore, there is an incentive in terms of performance to provide a link between stateof-the-art control methods and human operation.