Servo Compensation Learning Under Output Range Limits
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Solution Overview
Problem
In servo control devices, inappropriate compensation values can lead to unstable operation of machine tools, robots, or industrial machines, causing vibrations or shutdowns during machine learning, interrupting the learning process.
Innovation Solution
A machine learning device that limits compensation values within a set range, using reinforcement learning to optimize compensation values by applying rewards for values within the range and adjusting parameters to prevent inappropriate selections, ensuring continuous learning even when inappropriate values are chosen.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If machine learning is performed while actually operating the machine tool to learn compensation values, then the learning effectiveness is improved, but inappropriate compensation values may cause vibration or shutdown, interrupting the learning process
Solution Approach 1:
The patent applies preliminary anti-action by establishing a monitoring mechanism that detects inappropriate compensation values before they cause vibration or shutdown. The system proactively identifies when compensation values fall outside appropriate ranges and takes preventive action by adjusting or limiting these values, thereby preventing the harmful effects that would interrupt the learning process.
Solution Approach 2:
The patent implements feedback by continuously monitoring the compensation values generated during machine learning and comparing them against predetermined appropriate ranges. When inappropriate values are detected, the system provides feedback to adjust the learning process or limit the compensation values, ensuring that the learning continues without interruption while maintaining system stability.
2Manufacturing precision
If high-order transfer function is used to generate compensation values, then the control precision is improved, but the complexity of machine learning increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the parameters of the transfer function during the machine learning process. Instead of using a fixed high-order transfer function, the system modifies the function's parameters based on learned patterns and performance feedback, thereby maintaining high control precision while reducing the effective complexity of the learning task through adaptive parameter optimization.
Data Source
AI summary
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.