A system for controlling an electric motor which includes three coils and a rotor, comprising a motion-profile-generator for generating a rotor-motion-profile and for producing a position-command, a position-controller for determining a velocity-command and a position-feedforward, for determining a forward-velocity according to the prediction of the velocity required to reach said position-command. The system further includes a first summer for producing a modified velocity, a velocity controller, for determining a current-command, a velocity feedforward, for determining a forward-current and a second summer for producing a modified-current. The system also includes a commutator, for determining respective modified-coil-currents for each of at least three current-control-loops and for dividing said modified-coil-currents between the said current-control-loops according to the position of said rotor. Each current-control-loop includes a current-controller, for determining a respective voltage-command for the respective coil thereof an h-bridge for providing said voltage command to the respective coil thereof.

Motion control of a robot arm is performed via a reducer connected to a motor. A controller thereof includes a thrust control unit that generates motor position command value based on an input thrust command value, and a motor control unit that generates a current value based on the motor position command value. The motor control unit feeds back a motor position detected by a motor encoder, and the thrust control unit feeds back thrust detected by a thrust meter. The feedback from the motor control unit suppresses vibration phenomena at the reducer, and the feedback from the thrust control unit suppresses transmission error, thereby enabling motion control of the arm with rapidity and precision.

A machine learning device performs machine learning with respect to a servo control device including a velocity feedforward calculation unit. The machine learning device comprises: a state information acquisition unit configured to acquire from the servo control device, state information including at least position error, and combination of coefficients of a transfer function of the velocity feedforward calculation unit; an action information output unit configured to output action information including adjustment information of the combination of coefficients included in the state information, to the servo control device; a reward output unit configured to output a reward value in reinforcement learning based on the position error included in the state information; and a value function updating unit configured to update an action value function on the basis of the reward value output by the reward output unit, the state information, and the action information.

Motion control of a robot arm is performed via a reducer connected to a motor. A controller thereof includes a thrust control unit that generates motor position command value based on an input thrust command value, and a motor control unit that generates a current value based on the motor position command value. The motor control unit feeds back a motor position detected by a motor encoder, and the thrust control unit feeds back thrust detected by a thrust meter. The feedback from the motor control unit suppresses vibration phenomena at the reducer, and the feedback from the thrust control unit suppresses transmission error, thereby enabling motion control of the arm with rapidity and precision.

A numerical controller is provided with a speed feedforward gain correction unit configured to obtain an associated axis, which is subject to a varying load applied to a particular axis according to a coordinate value, and a correction coefficient of the particular axis corresponding to the current coordinate value of the associated axis, based on a correction coefficient storage unit, and correct a speed feedforward gain for speed feedforward control of the particular axis, and a motor control unit configured to control the particular axis based on the corrected speed feedforward gain.