Abstract: A machine learning device acquires, as a label, a command output by a servo control apparatus to a control target device so as to drive and control the control target device. The machine learning device acquires, as input data, an output of the control target device driven based on the command, and constructs a learning model relating to feedforward control for correcting the command, by performing supervised learning by use of a set of the label and the input data serving as teaching data.

Abstract: A motor control device for controlling a servomotor to axially move a movement target object includes: a speed detector for detecting the movement speed of the movement target object; an abnormality detector for detecting an abnormality of the speed detector; a motor controller for performing deceleration control on the servomotor to decelerate the movement target object, upon detection of the abnormality; a reference speed generator for generating a reference speed that decreases with passage of time, based on the movement speed when the movement target object decelerates and a predetermined deceleration; a speed monitor for monitoring the movement speed and determining whether or not the movement speed is equal to or greater than the reference speed; and a brake controller for actuating a brake for braking axial movement of the movement target object when the movement speed is determined to be equal to or greater than the reference speed.

Abstract: A motor drive system includes a converter configured to convert power between AC power in a power source and DC power in a DC link, an inverter for drive configured to convert power between the DC power and AC power in a servomotor for drive, a motor control unit for drive configured to control the servomotor for drive, a power storage device configured to store the DC power from the DC link or supplies the DC power to the DC link, and a determination unit configured to determine whether the holding energy of the power storage device is lower than a threshold for energy shortage determination, wherein when the holding energy is lower than the threshold for energy shortage determination, the motor control unit for drive controls the servomotor for drive by setting an additional standby period in which the servomotor for drive is inactive in a predetermined operation pattern.

Abstract: The settling time of machine learning is shortened. A machine learning device is configured to perform machine learning related to optimization of coefficients of a transfer function of an IIR filter of a feedforward calculation unit with respect to a servo control device configured to control a servo motor configured to drive an axis of a machine tool, a robot, or an industrial machine using feedforward control by a feedforward calculation unit having the IIR filter. The machine learning device represents a zero-point at which the transfer function of the IIR filter is zero and a pole at which the transfer function diverges infinitely in polar coordinates using a radius r and an angle ?, respectively, and searches for and learns, within a predetermined search range, the radius r and the angle ? to thereby perform the optimization of the coefficients of the transfer function of the IIR filter.

Abstract: To provide a servo controller for an industrial machine allowing construction of a system achieving more excellent power efficiency than a conventional system. A servo controller includes: a driving motor that drives an industrial machine; a load detecting unit that detects a load on the driving motor or the amount of power consumed by the driving motor; a buffer motor that feeds regenerative power to the driving motor on the basis of a result of the detection by the load detecting unit; and a base speed setting unit for recovering the buffer motor to a second base speed set to be lower than a constant first base speed preset for the buffer motor and applied before the regenerative power is fed to the driving motor after the buffer motor is decelerated from the first base speed and the regenerative power is fed to the driving motor.

Abstract: 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.

Abstract: A motor controller includes: a command unit which outputs a command value for controlling a motor that drives a driven unit; a motor control unit which controls the motor based on the command value; a compensation filter which compensates for the command value; and a preprocessing unit which is provided in a stage preceding the compensation filter, the compensation filter has a frequency region in which a gain is greater than 1 and the preprocessing unit executes, when a variation in the command value before being compensated for with the compensation filter is equal to or less than a predetermined value, preprocessing in which a past command value is used as a current command value.

Abstract: To provide a servo motor controller allowing to eliminate the risk of abnormal driving in a servo motor caused due to the inability to detect abnormality prior to establishment of absolute position. A device is configured to control a servo motor of an industrial machine. The device includes a position detection part configured to detect a position of the servo motor, a magnetic pole detection part configured to detect a magnetic pole position of the servo motor, and a pole position calculation part configured to, at least in initial calculation, obtain the magnetic pole position detected by the magnetic pole detection part as an initial magnetic pole position, prior to establishment of absolute position, and in the following calculation, incrementally obtain the magnetic pole position on the basis of data of the position detected by the position detection part and a magnetic pole interval of the motor.

Abstract: A controller (100, 100A) for easily evaluating validity of inertia is provided. A controller (100, 100A) includes: an electric motor (300); an actual operation acquisition unit (301) that acquires an actual operation of the electric motor (300); a model unit (108) that estimates an operation of the electric motor (300) from a current value applied to the electric motor (300) using a model including inertia of the electric motor (300) and a driven body (400) connected to the electric motor (300); an operation signal input unit (106) that applies an operation signal to a control loop of the electric motor (300) for a prescribed period; and an evaluation value calculation unit (111) that calculates an evaluation value for evaluating the inertia on the basis of a difference between an actual operation and an estimated operation in the application period of the operation signal.

Abstract: An object is to read the information of a feature shape included in a machining program so as to calculate a control command suitable for machining processing on the feature shape. A numerical controller (300) includes: a feature detection unit (302) which detects the feature of a machined shape from a machining program that commands the movement of a tool or a workpiece; an inward-turning amount calculation unit (303) which calculates, based on a servo parameter of a servo controller (400) that drives the tool or the workpiece, the feature of the machined shape detected from the machining program and a machining requirement that specifies a machining condition, a relation formula that determines the inward-turning amount of a machining path with respect to a program path; and a feedrate determination unit (304) which determines a feedrate that is optimized with the relation formula.

Abstract: A motor control device includes an acceleration detecting section configured to detect an acceleration of a control object, and an acceleration control section configured to control an acceleration of a motor driving the control object based on the detected acceleration, in which the acceleration control section includes a vibration component extraction filter configured to extract a vibration component generated between the motor and the control object, and the vibration component extraction filter changes a filter characteristic frequency according to at least one of a position and a mass of the control object.

Abstract: A control device includes: an output unit configured to select a motor and output a drive command to a motor drive unit that should be connected to the selected motor so that the selected motor executes a predetermined feed operation; an acquisition unit configured to acquire feedback information from each of the multiple motor drive units; and a wire connection determination unit configured to determine, based on the feedback information, whether the selected motor is connected to the motor drive unit that should be connected to the selected motor, by a power line and a feedback line.

Abstract: A motor control device includes: a position command section configured to generate a position command for a control object; a position detecting section configured to detect a position of the control object or a position of a motor configured to drive the control object; and a position control section configured to control a position of the motor based on the position command and the detected position of the control object or the motor, in which at least one of the position command section and the position control section includes a vibration suppression filter configured to approximate a reverse characteristic of a vibration characteristic generated between the motor and the control object, and the vibration suppression filter changes a vibration suppression frequency according to at least one of the position and a mass of the control object.

Abstract: A machine learning device that performs machine learning with respect to a changing unit configured to change a parameter of a control unit configured to control a servo motor and a compensation value of at least one of a position command and a torque command includes: a state information acquisition unit configured to acquire state information including the position command, a positional error, a combination of the parameter and the compensation value; an action information output unit configured to output action information including adjustment information of the combination of the parameter and the compensation value included in the state information; a reward output unit configured to output a reward value of reinforcement learning based on the positional error included in the state information; and a value function updating unit configured to update a value function based on the value of the reward, the state information, and the action information.

Abstract: A motor drive apparatus includes a converter; an inverter for drive; a power storage device configured to supply DC power to a direct current link or to store DC power from the direct current link; a power consumption estimation unit configured to acquire a power consumption estimation value which is an estimation value of a total power consumption at a time point later, by a predetermined time, than a value at a present time point, the total power consumption being obtained as a sum of an output of the servomotor for drive, a winding loss in the servomotor for drive, a loss in the converter and a loss in the inverter for drive; and a power storage device control unit configured to control power supply and power storage of the power storage device in accordance with the power consumption estimation value.

Abstract: A machine learning device that performs reinforcement learning for a servo control device and optimizes a coefficient of a filter for attenuating a specific frequency component provided in the servo control device includes a state information acquisition unit which acquires state information that includes the result of calculation of at least one of an input/output gain of the servo control device and a phase delay of input and output, the coefficient of the filter and conditions, and an action information output unit which outputs, to the filter, action information including adjustment information of the coefficient. A reward output unit determines evaluation values under the conditions based on the result of the calculation to output, as a reward, the value of a sum of the evaluation values. A value function updating unit updates an action value function based on the value of the reward, the state information and the action information.

Abstract: A spindle vibration measuring system which measures vibration of a spindle in a machining device that performs a cutting or abrading process on a workpiece. The machining device has a workpiece holder that holds the workpiece, the spindle that holds a tool, and a moving mechanism that relatively moves the workpiece holder and the spindle. The spindle vibration measuring system acquires positional variation data or vibration data of the moving mechanism when the spindle rotates, and a result related to vibration of the spindle to output or store based on the positional variation data or the vibration data.

Abstract: 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.

Abstract: A motor drive system includes: a converter connected to a DC link; an inverter for drive connected to the DC link; a power storage device configured to store a DC power from the DC link or supplies a DC power to the DC link; a torque limit value calculation unit configured to calculate a torque limit value of a servomotor for buffer in the power storage device on the basis of a rotation speed of the servomotor for buffer and a DC power amount stored or supplied by the power storage device; and a motor control unit for buffer configured to perform a torque control with respect to the servomotor for buffer while changing an upper limit value and a lower limit value of a torque command using the torque limit value so as to adjust a DC power amount stored or supplied by the power storage device.

Abstract: To perform reinforcement learning enabling to prevent complicated adjustment of coefficients of backlash compensation and backlash acceleration compensation.