Spatially Robust CD Web Control Tuning for Multiple Actuator Arrays
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Solution Overview
Problem
Tuning model predictive control (MPC) or other model-based controllers for cross-direction (CD) control in web manufacturing or processing systems with multiple actuator beams is challenging due to non-intuitive tuning parameters and the need for advanced control theory understanding, making automated tuning difficult and time-consuming.
Innovation Solution
The method involves spatial and temporal tuning of model-based controllers, using automated techniques to identify weighting matrices that suppress frequency components in actuator profiles and adjust parameters for optimal performance, allowing non-experts to provide intuitive information for tuning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated tuning algorithms relying on robust control theory are used, then control performance can be improved, but the complexity of the tuning process increases and requires advanced control theory understanding
Solution Approach 1:
The patent introduces an intermediary automated tuning algorithm that acts as a mediator between the user and the complex robust control theory. This algorithm translates intuitive user specifications about desired control performance into the appropriate controller parameters automatically, eliminating the need for users to directly engage with complex control theory while still achieving robust control performance.
Solution Approach 2:
The tuning algorithm performs self-service by automatically determining the controller parameters based on the process model and desired performance specifications. The algorithm independently handles the complex optimization and parameter selection that would otherwise require expert control theory knowledge, making the tuning process autonomous and accessible to non-experts.
2Ease of operation
If traditional MPC tuning parameters are used, then control implementation is straightforward, but the parameters are not intuitive and trial and error tuning is time-consuming
Solution Approach 1:
The patent transforms the traditional non-intuitive MPC tuning parameters into intuitive performance-based specifications. Instead of adjusting abstract control parameters through trial and error, users can now specify desired control performance in terms of intuitive parameters such as response time, overshoot limits, and steady-state accuracy. The automated algorithm then translates these intuitive specifications into the actual controller parameters, dramatically reducing tuning time while maintaining ease of operation.
3Adaptability or versatility
If multiple actuator arrays with multiple measurements are used, then control capability is enhanced, but the difficulty of achieving robust performance increases
Solution Approach 1:
The patent segments the complex multi-array control problem into manageable sub-problems by processing each actuator array and measurement channel independently through the automated tuning algorithm. The algorithm systematically handles the spatial relationships and interactions between multiple actuators and measurements by breaking down the overall control objective into individual channel optimizations that can be coordinated to achieve robust multi-array control performance.
Data Source
AI summary
A method includes obtaining one or more models associated with a model-based controller in an industrial process having multiple actuator arrays and performing spatial tuning of the controller. The spatial tuning includes identifying weighting matrices that suppress one or more frequency components in actuator profiles of the actuator arrays. The spatial tuning could also include finding a worst-case cutoff frequency over all output channels for each process input, designing the weighting matrices to penalize higher-frequency actuator variability based on the model(s) and the cutoff frequencies, and finding a multiplier for a spatial frequency weighted actuator variability term in a function that guarantees robust spatial stability. The controller could be configured to use a function during control of the industrial process, where a change to one or more terms of the function alters operation of the controller and the industrial process and at least one term is based on the weighting matrices.