Servo control device

Patent metadata

Field	Value
Publication number	US-2019361421-A1
Application number	US-201716080929-A
Country	US
Kind code	A1
Filing date	Nov 10, 2017
Priority date	Nov 10, 2017
Publication date	Nov 28, 2019
Grant date	—

Abstract

The present invention is a servo control device that controls a servomotor based on a command position. The servo control device includes a correction unit that corrects the command position using a first neural network that performs processing based on parameters representing a network structure, and a servo amplifier that controls the servomotor based on a corrected command position outputted from the correction unit. The correction unit corrects the command position based on the corrected command position and the actual position of the servomotor.

First claim

1 . A servo control device to control a servomotor based on a command position, the servo control device comprising:
a correction unit to correct the command position using a first neural network to perform processing based on parameters representing a network structure; and a servo amplifier to control the servomotor based on a corrected command position outputted from the correction unit, wherein the correction unit corrects the command position based on the corrected command position and an actual position of the servomotor.

2 . The servo control device according to claim 1 ,
wherein the correction unit predicts an actual position of the servomotor based on the corrected command position and the actual position of the servomotor, and corrects the command position based on a prediction result.

3 . The servo control device according to claim 1 , further comprising
a learning unit to determine the parameters based on the corrected command position and the actual position of the servomotor.

4 . The servo control device according to claim 3 ,
wherein the learning unit determines the parameters using a second neural network.

5 . The servo control device according to claim 4 ,
wherein the learning unit determines the parameters based on the corrected command position and a model position error representing an error between a model position that is an estimated actual position of the servomotor calculated using the corrected command position, and the actual position of the servomotor.

6 . The servo control device according to claim 3 ,
wherein the learning unit determines the parameters in a cycle different from a command value generation control cycle that is a cycle in which the command position is inputted and a servo control cycle that is a cycle in which the servo amplifier controls the servomotor.

7 . The servo control device according to claim 3 ,
wherein when the learning unit determines the parameters, the learning unit applies the determined parameters to the correction unit.

8 . The servo control device according to claim 3 , further comprising
a determination unit to determine a timing at which the parameters determined by the learning unit are applied to the correction unit, based on the command position and the actual position of the servomotor, wherein the learning unit applies the determined parameters to the correction unit according to a result of the determination by the determination unit.

9 . The servo control device according to claim 1 ,
wherein the correction unit comprises: an inference unit to predict an actual position of the servomotor based on the corrected command position and the actual position of the servomotor, and calculate a correction amount of the command position based on a prediction result; a first adder to add the correction amount calculated by the inference unit to the command position, thereby generating a corrected command position to be outputted to the servo amplifier; a delay unit to delay the command position and then input the command position to the first adder; and a second adder to add the correction amount calculated by the inference unit to the command position, thereby generating a corrected command position to be inputted to the inference unit.

Assignees

• Mitsubishi Electric Corp

Inventors

• Tsuda Takeshi
• Sato Goh
• Nishino Shinya

Classifications

• G06N3/045

  Combinations of networks · CPC title

• G05B2219/32335

  Use of ann, neural network · CPC title

• G05B19/404 Primary

  characterised by control arrangements for compensation, e.g. for backlash, overshoot, tool offset, tool wear, temperature, machine construction errors, load, inertia (G05B19/19, G05B19/41 take precedence) · CPC title

• G05B13/027

  using neural networks only · CPC title

• G06N3/0454

  Physics · mapped topic