To fulfil process-technical tasks, electric drives are used in automated production lines, power plants, centrifuges and cranes as well as in road and rail vehicles. Usually, the drives are operated in closed-loop control, whereby in addition to the actual fulfilment of the control objective, secondary aspects such as loss-reduced or sensorless operation are increasingly desired or even demanded by the operators. The state of the art is represented by innovative approaches in singular fields of control methods for electrical drives. Among others, advanced methods for current and torque control , temperature estimation , parameter identification, optimized pulse patterns  or self-commissioning of electrical drives can be mentioned. Typically, these methods are only applied to individual problems for specific applications. In some cases, it was possible to combine several methods for one specific application, e.g. artificial neural networks with particle swarm optimization for temperature monitoring, in order to further increase the quality, efficiency and reliability of the results obtained so far . A holistic control concept, which combines state-of-the-art methods as solutions for specific subproblems, has not yet been developed.