The research proposal aims to optimize the performance of electric machines through the utilization of automatic control and parameter adaptation, harnessing the power of machine learning algorithms. Furthermore, it addresses the issue of limited integration of machine learning and performance parameters in electric machines. The research will encompass data collection from electric machines under real operating conditions, the development of machine learning algorithms for data analysis and the creation of prediction and control models. Subsequently, these algorithms will be implemented in real-time monitoring of the machines operation and will adapt their parameters based on changes in operating conditions.