Multi-Axis Feedforward Control for Faster Parameter Tuning
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Solution Overview
Problem
Existing multi-axis systems face challenges in optimizing closed-loop control behavior due to manual and error-prone parameterization of feedforward control units, leading to mechanical distortion and reduced precision in positioning tasks.
Innovation Solution
An automated method for identifying and parameterizing feedforward control parameters using actual identification variables, which are determined by identification units associated with closed-loop control units, improving the closed-loop control behavior and enhancing precision in multi-axis systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual parameterization of feedforward control units is used, then control behavior can be adjusted, but the process is time-consuming and prone to errors
Solution Approach 1:
The system performs self-identification of feedforward control parameters automatically without requiring manual intervention. The identification unit uses actual identification variables from sensors to automatically determine optimal parameters, making the system serve itself rather than requiring external manual configuration.
Solution Approach 2:
The patent replaces manual mechanical parameterization processes with an automated electronic identification system. The identification unit electronically processes actual identification variables to determine feedforward control parameters, substituting human-operated mechanical adjustment with automated electronic computation.
2Ease of operation
If manual parameterization is used, then some control adjustment is possible, but errors can lead to mechanical damage
Solution Approach 1:
The system continuously monitors actual identification variables from sensors and uses this feedback to automatically adjust feedforward control parameters. This closed-loop feedback mechanism ensures that parameter adjustments are based on real system behavior, preventing erroneous manual adjustments that could cause mechanical damage.
Solution Approach 2:
The identification unit automatically monitors system performance and adjusts parameters without manual intervention, eliminating human errors that could lead to harmful effects. The system serves itself by continuously optimizing parameters based on actual operational data.
3Productivity
If automated identification is implemented, then parameterization speed improves, but system complexity increases
Solution Approach 1:
The identification unit serves multiple functions: it processes actual identification variables, determines feedforward control parameters, and integrates with existing closed-loop control units. This multi-functionality achieves automated parameterization without requiring entirely separate dedicated systems, thereby limiting the increase in overall system complexity.
Solution Approach 2:
The identification unit acts as an intermediary between sensors and control units, processing actual identification variables and generating feedforward control parameters. This intermediary component simplifies the overall architecture by providing a single integration point rather than requiring direct complex connections between multiple subsystems.
4Manufacturing precision
If feedforward control is added to improve control behavior, then following error behavior improves, but control loop stability may be endangered
Solution Approach 1:
The feedforward control component performs preliminary action by anticipating required control adjustments based on actual identification variables before closed-loop control responds to errors. This preliminary action improves following error behavior while maintaining stability because the feedforward component is parameterized to complement rather than conflict with closed-loop control actions.
Solution Approach 2:
The system optimizes the parameters of the feedforward control unit through automated identification to achieve the best balance between improving following error behavior and maintaining control loop stability. By automatically tuning parameters like acceleration-proportional and speed-proportional components, the system adapts to specific mechanical characteristics without requiring manual stability analysis.
Data Source
AI summary
In order to provide an optimized multi-axis system having mechanically coupled axes, a feedforward control identification process is provided, during which actual identification variables occurring in each case at the motor are each provided to identification units associated with the feedforward controllers, wherein feedforward control parameters are identified using the actual identification variables, and closed-loop controllers are parameterized using the feedforward control parameters.