Method for controlling the charging pressure of a turbocharger (200, 300) with a variable turbine geometry of an internal combustion engine, the controller parameters (p) of which vary during the control of a controlled system with a controller as a function of variables (s) of the controlled system, characterized in that • in order to determine the controller parameters (p) as a function of the variables (s) of the controlled system Gaussian process models are used to determine the controller parameters (p) in a device which is designed for the purpose, wherein the determined controller parameters (p) are the outputs of the Gaussian process models, • wherein status variables (x; x1, x2, x3, x4, x5) which are input into the controlled system and which are fed back to the controller are estimated or measured by means of an observer as a function of manipulated variables (u; u1, u2, u3) which act on the controlled system, wherein the observer also models gain factors by means of Gaussian process models within an estimate amplifier, • wherein, for the estimation of the status variables (x; x1, x2, x3, x4, x5) of the controlled system, the observer contains a model which outputs the status variables (x; x1, x2, x3, x4, x5) and modelled measurement variables (m') to the controller, wherein available measurement variables (m) of the controlled system are subtracted from the modelled measurement variables (m') of the model, after which as a result a measurement error or an error signal (f) is fed to the estimate amplifier, • wherein the plurality of Gaussian process models of the estimate amplifier generate gain factors and manipulated variables (u') of the observer, with the result that complete feedback of the status variables (x; x1, x2, x3, x4, x5) of the controlled system is carried out by the observer, • wherein the gain factors bring about, within the estimate amplifier in the structure of the observer, convergence of an estimate error by generating an additional actuation portion (u'). • in order to determine the controller parameters (p) as a function of the variables (s) of the controlled system Gaussian process models are used to determine the controller parameters (p) in a device which is designed for the purpose, wherein the determined controller parameters (p) are the outputs of the Gaussian process models, • wherein status variables (x; x1, x2, x3, x4, x5) which are input into the controlled system and which are fed back to the controller are estimated or measured by means of an observer as a function of manipulated variables (u; u1, u2, u3) which act on the controlled system, wherein the observer also models gain factors by means of Gaussian process models within an estimate amplifier, • wherein, for the estimation of the status variables (x; x1, x2, x3, x4, x5) of the controlled system, the observer contains a model which outputs the status variables (x; x1, x2, x3, x4, x5) and modelled measurement variables (m') to the controller, wherein available measurement variables (m) of the controlled system are subtracted from the modelled measurement variables (m') of the model, after which as a result a measurement error or an error signal (f) is fed to the estimate amplifier, • wherein the plurality of Gaussian process models of the estimate amplifier generate gain factors and manipulated variables (u') of the observer, with the result that complete feedback of the status variables (x; x1, x2, x3, x4, x5) of the controlled system is carried out by the observer, • wherein the gain factors bring about, within the estimate amplifier in the structure of the observer, convergence of an estimate error by generating an additional actuation portion (u').