Systems, methods and devices for approximate dynamic programming vector controllers for operation of IPM motors in linear and over modulation regions

A method for controlling an interior-mounted permanent magnet (IPM) alternating-current (AC) electrical machine by:

• providing a pulse-width modulated (PWM) converter operably connected between an electrical power source and the IPM AC electrical machine;
• providing a neural network vector control system operably connected to the PWM converter, the neural network vector control system comprising a current-loop neural network configured to implement an approximate dynamic programming (ADP) algorithm, wherein the current-loop neural network is trained to minimize a cost function of the ADP algorithm using a forward accumulation through time (“FATT”) algorithm;
• receiving a plurality of inputs at the current-loop neural network;
• outputting a first compensating dq-control voltage from the current-loop neural network, wherein the current-loop neural network is configured to optimize the first compensating dq-control voltage based on the plurality of inputs;
• providing a feedforward controller operably connected to the PWM converter;
• receiving reference current inputs at the feedforward controller, wherein the inputs at the feedforward controller comprise a reference d-axis current, isd*, and a reference q-axis current, isq*;
• outputting a second compensating dq-control voltage from the feedforward controller, wherein the feedforward controller is configured to regulate the second compensating dq-control voltage based on the reference current inputs;
• and
• controlling the PWM converter using the first compensating dq-control voltage and the second compensating dq-control voltage,
• wherein the feedforward controller is designed based on default parameters of the IPM AC electrical machine.