Roll Stand Flatness Actuator Optimization Under Boundary Constraints
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Solution Overview
Problem
Current flatness control methods for metal strips in roll stands are prone to inaccuracies, time-consuming, and fail to account for boundary conditions, leading to suboptimal operation and increased wear on actuators, with existing methods unable to actuate flatness actuators independently or simultaneously optimize multiple actuators effectively.
Innovation Solution
Implementing a first optimizer that determines current correction values by minimizing the deviation from target flatness while considering linear ancillary conditions, using an effectiveness matrix to calculate manipulated variables for flatness actuators, and incorporating a flatness controller to adjust these variables in real-time, allowing for online optimization and rapid adaptation to changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional flatness control methods are used, then the control process is simple, but the control precision and flatness accuracy deteriorate
Solution Approach 1:
The control system is segmented into multiple independent flatness actuators (C1, C2, ..., Cn), each controlled by dedicated manipulated variables. The optimization problem is divided into determining individual correction values for each actuator based on their specific effectiveness coefficients, allowing precise control of different regions of the metal strip while maintaining manageable system complexity through modular structure
Solution Approach 2:
The system dynamically determines manipulated variables by changing parameters such as correction values (s1, s2, ..., sn) for each flatness actuator based on measured flatness deviations. The effectiveness coefficients (w11, w12, ..., wnn) serve as key parameters that quantify the influence of each actuator, allowing the system to adapt control parameters in real-time to achieve target flatness while managing complexity through parameter-based control
2Manufacturing precision
If multiple flatness actuators are optimized simultaneously, then the overall flatness control improves, but the computation time and processing complexity increase
Solution Approach 1:
The system performs preliminary determination of manipulated variables for multiple flatness actuators simultaneously before actual rolling operations. By calculating all correction values (s1, s2, ..., sn) in advance based on measured deviations and effectiveness coefficients, the system prepares the optimal control state ahead of time, enabling rapid execution during production without real-time computation delays
Solution Approach 2:
The system uses a mathematical model that copies the physical relationships between actuators and flatness outcomes through effectiveness coefficients. This virtual model allows simultaneous optimization of multiple actuators by solving a system of linear equations rather than requiring complex real-time iterative calculations, significantly reducing computation time while maintaining control precision
3Productivity
If flatness actuators are actuated without considering boundary conditions, then the control response is fast, but the wear on actuators increases
Solution Approach 1:
The system incorporates feedback by measuring actual flatness deviations and using this information to determine appropriate correction values for each actuator. The measured flatness values feed into the optimization calculation, which then determines manipulated variables that respect actuator boundaries. This closed-loop feedback ensures actuators are actuated only when and how necessary, reducing unnecessary wear while maintaining fast response to actual flatness deviations
Solution Approach 2:
The system dynamically adjusts the actuation of each flatness actuator based on real-time conditions and measured deviations. By determining individual correction values (s1, s2, ..., sn) for each actuator based on their specific effectiveness and current flatness errors, the system optimizes the dynamic behavior of each actuator, actuating them only to the extent necessary to achieve target flatness, thereby reducing wear while maintaining rapid response capability
4Productivity
If conventional control methods are used, then the system is easy to operate, but the operational efficiency and productivity deteriorate
Solution Approach 1:
The control system performs self-service by automatically determining the optimal manipulated variables for multiple flatness actuators based on measured flatness deviations and pre-stored effectiveness coefficients. The system autonomously calculates correction values (s1, s2, ..., sn) without requiring manual intervention or complex operator decisions, thereby significantly improving operational efficiency and productivity while maintaining ease of operation through automated control
Data Source
AI summary
A metal strip is rolled in a roll stand and a control device for the roll stand determines, by means of a working cycle, a number of manipulated variables for flatness actuators of the roll stand and actuates them accordingly. The control device implements an optimizer, which provisionally sets the current correction values, and determines a totality of flatness values. Then, the optimizer minimizes the relationship by varying the current correction variables. When determining the current correction variables (s), the optimizer considers linear ancillary conditions, based at least in part on a vector having the ancillary conditions upheld by the current correction values and a vector having the ancillary conditions upheld by the difference of the current correction values relative to the correction values of the preceding working cycle. The control device determines the manipulated variables for the flatness actuators in consideration of the determined current correction variables.