Predictive Strip Position Control for Rolling Mill Threading
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Solution Overview
Problem
Existing roll train systems face challenges in maintaining the stability and planarity of metal strips during the rolling process, particularly in the threading phase, due to asymmetric deformations and limited operator control over lateral position corrections, leading to off-center alignment and potential damage to the strip and equipment.
Innovation Solution
Implementing a model predictive controller that establishes a sequence of control commands to adjust roll gap wedges, optimizing the strip position by predicting future control actions and minimizing abrupt changes, ensuring the strip enters downstream devices centrally and reducing lateral migration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If side guides are set tightly to restrict lateral migration, then the metal strip is guided more stably, but the strip edges are ground off and the strip becomes braced
Solution Approach 1:
The patent replaces the mechanical side guide system with an optical measurement system (camera and image processing) combined with a predictive control algorithm. The capture device records strip position without physical contact, and the model predictive controller calculates optimal work roll adjustments to guide the strip centrally without mechanical constraints, thereby eliminating edge grinding while maintaining stability control.
2Speed
If operators manually correct strip position on sight, then immediate adjustment is possible, but the control is demanding, requires much experience, and often has little success
Solution Approach 1:
The system implements automatic self-correction through the model predictive controller that continuously processes camera data and autonomously calculates optimal work roll adjustments. The controller independently manages strip position correction without operator intervention, using automated image processing and predictive algorithms to maintain central strip alignment, thereby eliminating the need for experienced manual operation while achieving fast response.
3Reliability
If a model predictive controller establishes a sequence of control commands, then superior control response is achieved, but the device complexity increases
Solution Approach 1:
The model predictive controller pre-calculates a sequence of optimal control commands based on current strip position and predicted future states. By establishing the entire command sequence in advance rather than reacting individually to each deviation, the system achieves superior control response and reliability while managing complexity through predictive planning rather than complex real-time calculations.
Data Source
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 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.