Method for the computer-aided learning of a control or adjustment of a technical system using a quality function and training data

摘要

A method for the computer-aided learning of a control of a technical system is provided. An operation of the technical system is characterized by states which the technical system can assume during operation. Actions are executed during the operation and convert a relevant state into a subsequent state. The method is characterized in that, when learning the control, suitable consideration is given to the statistical uncertainty of the training data. This is achieved in that the statistical uncertainty of a quality function which models an optimal operation of the technical system is specified by an uncertainty propagation and is incorporated into an action selection rule when learning. By a correspondingly selectable certainty parameter, the learning method can be adapted to different application scenarios which vary in statistical requirements. The method can be used for learning the control of an operation of a turbine, in particular a gas turbine.