A machine learning device performs machine learning with respect to a plurality of servo control units corresponding to a plurality of axes. A first servo control unit related to an axis receiving interference includes a compensation unit that compensates for at least one of a position error, a velocity command, and a torque command of the first servo control unit based on at least one of a variable related to a position command and a variable related to position feedback information of a second servo control unit related to an axis generating the interference. The machine learning device acquires state information including first and second servo control information and a coefficient of the function, outputs action information and a reward value for reinforcement learning, and updates a value function on the basis of the reward value, the state information, and the action information.

A machine learning device performs machine learning related to optimization of a compensation value of a compensation generation unit with respect to a servo control device that includes a compensation generation unit configured to generate a compensation value to be added to a control command for controlling a servo motor and a limiting unit configured to limit the compensation value or the control command to which the compensation value is added so as to fall within a setting range. During a machine learning operation, when the compensation value or the control command is outside the setting range and the limiting unit limits the compensation value or the control command so as to fall within the setting range, the machine learning device applies the compensation value to the learning and continues with a new search to optimize the compensation value generated by the compensation generation unit.

An object is to provide a servo controller which constantly optimizes parameters according to the state of a machine. A servo controller for controlling an electric motor which drives the axis of an industrial machine includes: a state value derivation unit which derives, from an operation program and/or operation plan information of the industrial machine, the chronological or event-sequential data of the state value of the electric motor or a driven member that is operated with the electric motor; and a parameter change unit which changes at least one parameter of a velocity gain, a position gain, a feedforward gain, a filter frequency and an acceleration/deceleration time constant after interpolation based on the chronological or event-sequential data derived in the state value derivation unit either chronologically or event-sequentially.

The present disclosure provides a servo motion control method and apparatus, as well as a robot using the same. The method includes: obtaining position parameters of a plurality of control vertices of a servo in a constant speed motion; creating a first smooth trajectory equation of the servo to move from the starting point to the ending point based on the position parameters of the plurality of control vertices; and controlling the servo to move based on the first smooth trajectory equation. The present disclosure is capable of realizing the smooth control of the motion of the servo from a starting position to an ending position, and avoiding the severe impacts during starting and stopping which affect the stability of the servo while the servo is in a constant high-speed motion.

A health monitor circuit for an electric machine is described. The health monitor circuit includes at least one sensor configured to measure a parameter of the electric machine, a communication interface, and a microprocessor coupled to the at least one sensor, the communication interface, and a memory. The microprocessor is configured to periodically collect time samples of the parameter measured by the at least one sensor, transmit factors of the time samples to the memory, and perform a high resolution fast-Fourier transform (FFT) on the factors. The microprocessor is also configured to extrapolate results of the high resolution FFT to a produce a high resolution frequency domain waveform, filter the high resolution frequency domain waveform by a parameter, and transmit, via the communication interface, the filtered frequency domain waveform to a remote system for further processing.

A controller includes a first transmission unit that transmits identification information designating one servo-motor from among the servo-motors, an operation detection unit that detects an operation aspect of the driving device that is caused by a movement of the drive section driven by the servo-motor which is operated by the drive controller based on the identification information transmitted by the first transmission unit, and a correspondence information generation unit that creates correspondence information indicating which servo-motor among the servo-motors the identification information transmitted by the first transmission unit corresponds to, based on the detected operation aspect.

A diverter system includes a diverter arm and an actuator assembly for operating and moving the diverter arm, wherein the diverter arm and the actuator assembly are configured such that the diverter arm is moveable between a retracted dwell position and a plurality of extended dwell positions within an impact dwell range.

Disclosed are a buffer material conveying and winding device, a buffer material conveying method and an assembly binding system, belonging to the technical field of a chip on glass. The buffer material conveying and winding device comprises a rack, a feed roller, a feed servo motor, a recycling roller, a recycling torque motor, a measuring device, a controller and an alarm. The controller may monitor whether the recycling length meets the requirement through the measuring device. The buffer material conveying method is based on the buffer material conveying and winding device. The assembly binding system comprises a buffer material conveying and winding device, a buffer material and a pressing head device.

The present invention is provided with: a servo motor; a servo driver which supplies a driving current to the servo motor and drives the servo motor; and an information processing device which transmits, to the servo driver, an operation command signal of the servo motor, wherein a movement range limiting device is further provided, which executes, on the basis of the operation command signal from the information processing device, automatic tuning that adjusts a gain in a servo motor control, and which prevents, in the automatic tuning, the servo motor from moving beyond a permissible range by returning the position of the servo motor to a prescribed start position.

Vibration of a machine end and an error of a moving trajectory are suppressed. A machine learning device performs machine learning of optimizing first coefficients of a filter provided in a motor controller that controls a motor and second coefficients of a velocity feedforward unit of a servo control unit provided in the motor controller on the basis of an evaluation function which is a function of measurement information after acceleration and deceleration by an external measuring instrument provided outside the motor controller, a position command input to the motor controller, and a position error which is a difference between the position command value and feedback position detection value from a detector of the servo control unit.