Model Inversion Iterative Learning Control for Printer Tracking
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Solution Overview
Problem
Existing printing control methods for large format printers rely on feedback control and iterative learning control, but they primarily focus on error correction for either the motor or the printing paper, leading to vibration and reduced tracking accuracy due to dependency on accurate system models and inability to balance error suppression between the two.
Innovation Solution
A model inversion-based iterative learning control method that simultaneously considers errors between the desired trajectory and actual displacement of the printing paper and the motor, using transfer functions to iteratively adjust the control compensation and reference input, constructing a multi-input and multi-output model inversion-based iterative learning control model to improve printing accuracy and robustness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If iterative learning control method is used to regulate printing-paper position, then tracking accuracy of printing paper is improved, but error of motor increases causing jitter or vibration
Solution Approach 1:
The control system is segmented into two independent control loops: one for motor position control and another for printing paper position control. This allows each loop to optimize its own performance without interfering with the other, resolving the contradiction between improving printing paper tracking accuracy and reducing motor error-induced vibration.
Solution Approach 2:
The motor position serves as an intermediary variable between the control input and the printing paper position. By independently controlling the motor position and using it as a reference for the printing paper position control, the system can achieve accurate printing paper tracking while maintaining smooth motor operation without direct conflict.
2Speed
If feedback control regulates motor-side position, then real-time control is achieved, but printing-paper position tracking accuracy is limited
Solution Approach 1:
The system performs preliminary action by using iterative learning control to pre-compensate for systematic errors in the printing paper position based on historical data. This preliminary correction, combined with real-time feedback control, achieves both fast response and high accuracy without waiting for error accumulation.
Solution Approach 2:
The system implements dual feedback mechanisms: real-time feedback control for immediate response to disturbances, and iterative learning feedback for progressive improvement of tracking accuracy over multiple cycles. This combination resolves the contradiction between real-time response capability and long-term tracking precision.
Data Source
AI summary
A model inversion-based iterative learning control method for a printer and a printer system. An error of a desired trajectory and an actual displacement of a printing paper and an error of a reference input and an actual displacement of a motor are considered at the same time to construct an iterative learning control model for the printer based on an inversion model, so as to iteratively modify an error failing to meet requirements.