Reinforcement Learning-Based Controller for Field-Oriented Control of Induction Machine

This paper presents the concept of reinforcement learning-based field-oriented control (FOC) of induction motor. Conventional controllers such as PID used for FOC of induction machines are model-based controllers and face the issue of parameter tuning. Periodic retuning of PID controllers is required to take care of model approximations, parameter variations of the system during operation and external disturbances which are random in character, magnitudes, and place of occurrences in the system. Reinforcement learning is a model-free and online learning technique which can take care of parameter variations. These properties make reinforcement learning a potential candidate, to act as an adaptive controller which can replace conventional controllers. In this study, reinforcement learning-based controller has been designed to control the speed of induction machine using filed-oriented control. The controller performance has been verified for various operating conditions by computer simulation in MATLAB/SIMULINK.