| Summary: | A key issue in paper-machine Cross-Directional (CD) Control is alignment. Typically, this mapping problem is a non-linear and slowly time-varying phenomenon for individual machines.
The first part of this thesis specifically focuses on different causes of the misalignment and reviews recent developments in CD mapping. It summarizes the results of a comprehensive survey of different alignment schemes that have been used in CD control processes.
This dissertation presents a novel, deterministic, tensor-based modeling of the closed loop controlled CD process and an alignment method. First, we link the CD data to the tensor model. Exploiting this link, we derive a deterministic blind PARAFAC decomposition as an alignment method. The proposed PARAFAC capitalizes on the physical location of the actuators, scanning databoxes and their temporal diversities. Its performance is verified in several simulations then tested, evaluated and implemented as an alignment tool on real industrial paper machine.
In the second section we present a new novel Adaptive Robust Control approach to the multivariable CD process of continuous web manufacturing. We have applied discretized Internal Model Control(IMC)-based classical Windsurfing to each individual separated spatial frequency. This approach allows the dynamical bandwidth of the closed-loop system to be increased progressively at each spatial frequency through an iterative control relevant system identification and control design procedure. The method deals with both model uncertainty and measurement noise issues.
We also have applied Discrete-time H-infinity Windsurfing to each individual separated spatial frequency, starting with an initial model and a robust stabilizing controller at each spatial frequency. This modified approach provides robust stability through iterations. The approach is evaluated through a number of simulation experiments.
Finally, in a closed-loop approach to modifying the existing industrial CD controller, the objective is turned to the modification of the Windsurfing method. An input signal is designed for the system identification and control design. The nu-gap approach to robust control is fed into the Windsurfing model. Since the nu-gap metric establishes the upper and lower bounds, this approach reduces the number of iterations before the design is completed.
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