1. A control system for controlling a complex, real process of a controlled system, comprising: a process control system; a set of controllers comprising controllers which were previously active, and at least one active controller; a principal controller configured for training simulators that are for simulating the controlled system, developing the set of controllers, testing the set of controllers on the simulators in order to find a best controller, and comparing the best controller with the at least one active controller for determining whether to replace the active controller with the best controller, wherein the principal controller is configured: for individually training the simulators in evolutionary fashion using a recurrent neural network; and so that, for each of the simulators, the training comprises defining a fitness for being optimized, and the defining of the fitness comprises determining a discrepancy in a forecast value from an actual value, wherein the control system is hierarchically split into a plurality of levels comprising: a first level that is implemented by the controlled system and represents the complex, real process that is to be controlled, a second level that is realized by the process control system and represents an interface to the complex, real process that is to be controlled, a third level that is realized by the at least one active controller and represents control of the complex, real process that is to be controlled, and a fourth level that is realized by the principal controller and represents a superordinate supervisor.