The problems of simplified synthesis of scalar energy efficient systems of frequency control induction motor are discussed. As a method to provide energy efficiency the method of special frequency control laws calculated for a given load range is considered. The calculation procedure of the frequency control law of induction motor is performed by iterative optimization, where the number of iterations reached thousands. So more appropriate simplified procedure for the method of control law forming is needed. This is suitable for engineering calculations. The hypothesis of «similarity» of control laws is introduced for motors with similar parameters of the equivalent circuit. Assumed that the control law (quasioptimal law) is obtained for one motor and it is applied to other with similar parameters of the equivalent circuit with a certain error. Identification of motors with similar parameters are performed via the selforganizing artificial neural networks (Kohonen map). The number of clusters is chosen according to the desired dispersion of the motor parameters, which is determined by deviation from the values of the optimization criterion extremum. The result is presented as hexagonal Kohonen map of 49 clusters, where each cluster has its own set of quasioptimal laws. Thus, it is enough to match the motor with a certain cluster (otherwise classify). As a result the motor get automatically the quasioptimal control law. The paper describes the procedure of the network forming and training. Еxamples of optimized control laws are given.