1. A method for controlling a process upon which a plurality of actuators act, the method comprising the steps of: calculating manipulated variables for the plurality of actuators, the manipulated variables being calculated in a control device from measured values of output quantities of the process; learning, in a neural network, actuator efficiencies which describe a dependence of changes in the output quantities on changes in the manipulated variables for each actuator; and sending the learned actuator efficiencies to the control device to improve the calculation of the manipulated variables, wherein the neural network has at least two hidden layers, weights of one of the at least two hidden layers of the neural network modeling current operating point parameters.