Reinforcement Learning Based Field Oriented Control Of An Induction Motor

Induction motors are well known in industrial applications due to their low cost and reduced maintenance. Vector control or field-oriented control is the most preferred and reliable control technique in industrial world. Field oriented control is based on conventional controllers such as PID mainly due to their simplest structure and low complexity. However, when they are subjected to external disturbances or internal parameter change, it is quite difficult for these conventional controllers to fulfill the control requirements. The purpose of this research is to design a suitable non-linear feedback controller of an induction motor based on reinforcement learning agent. The proposed controller uses only reference speed and the error (difference) between reference speed and the output as control inputs to produce a torque such that rotor speed tracks the reference speed. Reinforcement learning based speed control algorithm is implemented and overall analysis is carried out of the closed loop system. It is shown that the proposed controller is capable of controlling the outer loop which controls the speed of the induction motor by taking different actions based on the given state. The performance of the proposed control schemes is verified under various operating conditions using simulation results.