Motor Control Parameter Modeling for Automatic Operation Adjustment
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Solution Overview
Problem
Manual adjustment of motor control device parameters for machines is time-consuming and relies heavily on operator experience, making it difficult to specify the causal relationship between parameter sets and machine operations, leading to inefficient operation adjustments.
Innovation Solution
An operation adjustment system that generates a calculation model based on pairs of parameter sets and evaluation indices, allowing for the automatic generation of new parameter sets to update the model, thereby optimizing machine operations without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual adjustment of motor control device parameters is performed, then operator experience can be utilized for parameter selection, but the adjustment process becomes time-consuming and inefficient
Solution Approach 1:
The system performs self-adjustment by automatically generating parameter sets based on the calculation model and evaluation indices, eliminating the need for manual operator intervention. The operation adjustment device autonomously iterates through parameter optimization, allowing the system to serve itself rather than relying on external human operators.
Solution Approach 2:
The patent replaces the manual mechanical adjustment process with an automated computational system. Instead of operators manually tuning parameters based on experience, the system uses a calculation model processed by a processor to automatically generate and evaluate parameter sets, substituting human cognitive processes with computational algorithms.
2Measurement precision
If manual parameter adjustment is performed, then operator expertise can guide parameter selection, but the causal relationship between parameter sets and machine operations becomes difficult to specify
Solution Approach 1:
The system implements feedback by evaluating each generated parameter set against the calculation model and using the evaluation index results to refine subsequent parameter generation. This closed-loop feedback mechanism allows the system to learn from each iteration, systematically establishing causal relationships between parameter changes and machine operation outcomes.
Solution Approach 2:
The system performs preliminary analysis by building a calculation model that captures the relationships between parameters and machine operations before actual parameter adjustment begins. This preliminary modeling phase establishes the causal framework that guides subsequent parameter generation, preventing the loss of causal information during the adjustment process.
3Productivity
If automatic parameter generation is implemented, then adjustment efficiency is improved, but the system requires a calculation model and evaluation indices infrastructure
Solution Approach 1:
The operation adjustment device serves multiple functions: it generates parameter sets, evaluates them against the calculation model, iterates to optimize parameters, and outputs final parameter recommendations. This multi-functional design consolidates what could be separate complex systems into a single integrated device, achieving productivity gains without proportionally increasing overall system complexity.
Data Source
AI summary
An operation adjustment system includes estimation circuitry and generation circuitry. The estimation circuitry is configured to generate a calculation model based on a plurality of pairs of a parameter set and an evaluation index. The calculation model indicates a relationship between the parameter set and the evaluation index. The parameter set affects an operation of a motor control device. The evaluation index relates to a machine operated according to the parameter set by the motor control device. The generation circuitry is configured to generate a new parameter set based on the calculation model in order to update the calculation model with the new parameter set.