Motor Flux Controller Gain and Time Constant Optimization

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing motor control systems face challenges in optimizing the gain of the magnetic flux controller and time constant of the magnetic flux estimator, leading to unstable current control and transient phenomena during motor acceleration and deceleration, requiring significant operator effort for parameter adjustment.

Innovation Solution

A machine learning apparatus that observes state variables such as motor acceleration, jerk, and acceleration time to learn and adjust the gain and time constant of the magnetic flux controller and estimator using reinforcement learning, optimizing parameters for improved follow-up properties and reducing operator intervention.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Speed

If the gain of the magnetic flux controller is increased to improve follow-up property, then the response speed improves, but the current control becomes unstable

Engineering Contradiction:

Improveresponse speed of magnetic flux follow-upVSAvoidstability of current control

Core Design Contradiction:

SpeedVSStability of the object's composition

Solution Approach 1:

The patent applies parameter changes by dynamically adjusting the gain of the magnetic flux controller based on the operating state of the motor. The gain is not fixed but varies according to state variables such as motor speed and load conditions, allowing the system to achieve both fast response and stability across different operating points. This resolves the contradiction by making the gain adaptive rather than static.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent implements dynamics by introducing a variable gain structure where the magnetic flux controller's gain changes dynamically with the motor's operating state. This dynamic adjustment allows the controller to maintain optimal performance across varying conditions, achieving both rapid response when needed and stability when required, thus resolving the fundamental trade-off between response speed and control stability.

Inventive Principle:

Principle #15Dynamics

2Measurement precision

If the time constant of the magnetic flux estimator is adjusted to match actual motor characteristics, then the estimation accuracy improves, but manual adjustment time and effort increase

Engineering Contradiction:

Improveaccuracy of magnetic flux estimationVSAvoidtime and effort for parameter adjustment

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent applies self-service by enabling the magnetic flux estimator to automatically determine its own time constant based on actual motor operation data. The system performs self-identification by analyzing the relationship between excitation current and magnetic flux during motor operation, eliminating the need for manual parameter tuning. This resolves the contradiction by making the estimation system self-configuring rather than requiring operator intervention.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent implements feedback by using the estimated magnetic flux and actual motor performance data to continuously refine the time constant of the magnetic flux estimator. The system monitors the accuracy of flux estimation and adjusts the time constant accordingly, creating a closed-loop parameter optimization process that automatically improves estimation precision without manual intervention.

Inventive Principle:

Principle #23Feedback

3Manufacturing precision

If manual parameter adjustment is performed to optimize control performance, then the control accuracy improves, but the operator effort and time required increase

Engineering Contradiction:

Improvecontrol accuracy of motor parametersVSAvoidoperator effort for parameter optimization

Core Design Contradiction:

Manufacturing precisionVSEase of operation

Solution Approach 1:

The patent applies self-service by automating the parameter optimization process entirely. The magnetic flux controller and estimator automatically identify and adjust their parameters based on motor operation data, eliminating the need for operators to manually tune parameters. This resolves the contradiction by making the system self-optimizing, achieving high control accuracy without requiring operator expertise or time investment.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the manual mechanical adjustment process with an automated computational system. Instead of operators physically adjusting parameters based on observation and experience, the system uses algorithms to automatically determine optimal parameters through data analysis and mathematical identification, substituting human effort with automated intelligence.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS9977411B2Motor control apparatus with magnetic flux controller and machine learning apparatus and method therefor

Publication Date: 2018.05.22 FANUC LTD

AI summary

A machine learning apparatus that learns a condition associated with a gain of a magnetic flux controller and a time constant of a magnetic flux estimator in a motor control apparatus includes: a state observation unit that observes a state variable defined by at least one of data relating to an acceleration of a motor, data relating to a jerk of the motor, and data relating to an acceleration time of the motor; and a learning unit that learns the condition associated with the gain of the magnetic flux controller and the time constant of the magnetic flux estimator in accordance with a training data set defined by the state variable.