ML models for real-time hybrid systems

A correct system design can be systematically obtained from a specification model of a real-time system that integrates hybrid measurements In a realistic industrial environment, this has been carried out through complete Matlab / Simulink / Stateflow models. However, there is a widespread interest in carrying out that modeling resorting to Machine Learning models, which can be understood as Automated Machine Learning for Real-time systems that present some degree of hybridation. An AC motor controller which must be able to maintain a constant air flow through a filter is one of these systems. The article also discusses a practical application of the method for implementing a closed loop control system to show how the proposed procedure can be applied to derive complete hybrid system designs with ANN.