Model Predictive Controller for Strip Positioning Stability
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Solution Overview
Problem
Existing rolling train systems face challenges in maintaining the stability and flatness of metal strips during the threading phase due to asymmetrical deformation, leading to off-center positioning and potential damage, which is difficult to control manually and requires complex and experience-dependent methods.
Innovation Solution
Implementing a model-predictive controller that determines a sequence of positioning commands to adjust the roll gap wedge, optimizing control commands to ensure the strip head enters downstream devices centered and within predetermined deviations, using a prediction horizon to account for future interventions and minimize abrupt changes in thickness and lateral migration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If side guides are set tightly to limit lateral movement, then strip positioning stability is improved, but strip edges are damaged by one-sided grinding
Solution Approach 1:
The control system performs preliminary actions by predicting future strip positions and adjusting roll gap wedge in advance to prevent excessive lateral wander before it occurs, rather than relying on tight side guides that cause mechanical damage
Solution Approach 2:
The patent replaces the mechanical constraint system (tight side guides) with a control system that uses model-predictive control and roll gap wedge adjustment to achieve positioning stability without mechanical contact that causes edge damage
2Ease of operation
If manual correction of work roll inclination is used, then strip straight running can be influenced, but control requires considerable experience and has limited success
Solution Approach 1:
The control system performs self-service by automatically determining optimal work roll inclination adjustments based on detected strip position and model predictions, eliminating the need for experienced operators to manually correct strip running
Solution Approach 2:
The system uses feedback from detection devices that continuously monitor strip position to automatically adjust work roll inclination, replacing experience-dependent manual correction with automated closed-loop control
3Manufacturing precision
If model-predictive control with sequence optimization is implemented, then control precision is improved, but control device complexity increases
Solution Approach 1:
The control sequence is segmented into discrete time steps within a prediction horizon, allowing the optimizer to determine optimal control commands for each step rather than treating control as a continuous complex problem
Data Source
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AI summary
When the strip head (7) of a metal strip (1) runs out of a roll stand (2a), a lateral position (y) of the strip head (7) is detected by means of a detection device (8) at at least one location (P) lying between the roll stand (2a) and a device (8) arranged downstream of the roll stand. A strip position controller (10) is designed as a model predictive controller which ascertains a sequence of adjusting commands (uk) to be output one after the other in a work cycle (T) on the basis of the detected lateral position (y) of the strip head (7), and the sequence is used to adjust a respective roll gap wedge. The number of control commands (uk) define a prediction horizon (PH) of the strip position controller (10) in connection with the work cycle (T). The strip position controller (10) at least supplies the roll stand (2a) with the control command (u0) ascertained to be output next.